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  <title>100 days of data</title>

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  <copyright>© 2026 100 days of data</copyright>
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  <itunes:author>Sven Sommerfeld</itunes:author>
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  <description><![CDATA[<p>🎙️ 100 Days of Data — Learn, Explore, Evolve<br><br>Welcome to 100 Days of Data, a podcast and learning journey exploring how data, AI, and digital transformation are changing the way we live, work, and lead.<br><br>Hosted by Sven, a technology and business leader passionate about turning insights into impact, each episode dives into real-world applications of data and artificial intelligence — without the buzzwords.<br><br>Here, you’ll find:<br>1) Thoughtful conversations about AI, analytics, and automation<br>2) Insights on digital leadership and innovation<br>3) Reflections on how humans and technology can grow together<br>4) Practical takeaways you can apply in your own work and learning journey<br><br>Whether you’re a data enthusiast, business leader, or just curious about the future, this channel will inspire you to learn something new — one day, one idea, one story at a time.<br><br>🔔 Subscribe and join the journey toward a smarter, more data-driven world.</p>]]></description>
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    <itunes:title>Episode 99 - Advanced Topic: AI + Creativity</itunes:title>
    <title>Episode 99 - Advanced Topic: AI + Creativity</title>
    <itunes:summary><![CDATA[In Episode 42 of 100 Days of Data, Jonas and Amy explore JSON.stringify(), the essential JavaScript function that converts complex data structures into JSON strings for seamless data exchange. They explain how this powerful tool packages data like a well-packed suitcase, making it easy to send across systems in formats that are readable and usable. The hosts discuss practical examples from retail, finance, and healthcare, highlighting real-world challenges such as handling functions, circular...]]></itunes:summary>
    <description><![CDATA[In Episode 42 of 100 Days of Data, Jonas and Amy explore JSON.stringify(), the essential JavaScript function that converts complex data structures into JSON strings for seamless data exchange. They explain how this powerful tool packages data like a well-packed suitcase, making it easy to send across systems in formats that are readable and usable. The hosts discuss practical examples from retail, finance, and healthcare, highlighting real-world challenges such as handling functions, circular references, and sensitive information. Listeners learn about the optional replacer and space arguments that customize serialization and improve readability. Jonas and Amy emphasize the importance of understanding JSON.stringify()’s limitations and pairing it with JSON.parse() for effective data workflows, critical for anyone working with APIs or AI projects aiming for scalable, reliable integrations.]]></description>
    <content:encoded><![CDATA[In Episode 42 of 100 Days of Data, Jonas and Amy explore JSON.stringify(), the essential JavaScript function that converts complex data structures into JSON strings for seamless data exchange. They explain how this powerful tool packages data like a well-packed suitcase, making it easy to send across systems in formats that are readable and usable. The hosts discuss practical examples from retail, finance, and healthcare, highlighting real-world challenges such as handling functions, circular references, and sensitive information. Listeners learn about the optional replacer and space arguments that customize serialization and improve readability. Jonas and Amy emphasize the importance of understanding JSON.stringify()’s limitations and pairing it with JSON.parse() for effective data workflows, critical for anyone working with APIs or AI projects aiming for scalable, reliable integrations.]]></content:encoded>
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    <pubDate>Wed, 08 Apr 2026 09:00:04 +0300</pubDate>
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    <itunes:title>Episode 98 - Advanced Topic: Climate AI</itunes:title>
    <title>Episode 98 - Advanced Topic: Climate AI</title>
    <itunes:summary><![CDATA[In Episode 12 of '100 Days of Data,' Jonas and Amy demystify JSON.stringify(), a vital JavaScript method that converts complex data objects into JSON strings. They explain how this serialization process enables easy data transfer across systems — from e-commerce shopping carts to connected cars and healthcare apps. The episode covers JSON’s structure, practical use cases, customization options, and common pitfalls like data loss with functions or undefined values. Jonas and Amy also highlight...]]></itunes:summary>
    <description><![CDATA[In Episode 12 of &apos;100 Days of Data,&apos; Jonas and Amy demystify JSON.stringify(), a vital JavaScript method that converts complex data objects into JSON strings. They explain how this serialization process enables easy data transfer across systems — from e-commerce shopping carts to connected cars and healthcare apps. The episode covers JSON’s structure, practical use cases, customization options, and common pitfalls like data loss with functions or undefined values. Jonas and Amy also highlight the importance of coupling JSON.stringify() with JSON.parse() for smooth data serialization and deserialization, emphasizing the method’s role as a bridge between human-readable code and machine communication. This insight helps both technical and non-technical listeners understand the invisible data flows powering modern applications and APIs.]]></description>
    <content:encoded><![CDATA[In Episode 12 of &apos;100 Days of Data,&apos; Jonas and Amy demystify JSON.stringify(), a vital JavaScript method that converts complex data objects into JSON strings. They explain how this serialization process enables easy data transfer across systems — from e-commerce shopping carts to connected cars and healthcare apps. The episode covers JSON’s structure, practical use cases, customization options, and common pitfalls like data loss with functions or undefined values. Jonas and Amy also highlight the importance of coupling JSON.stringify() with JSON.parse() for smooth data serialization and deserialization, emphasizing the method’s role as a bridge between human-readable code and machine communication. This insight helps both technical and non-technical listeners understand the invisible data flows powering modern applications and APIs.]]></content:encoded>
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    <pubDate>Tue, 07 Apr 2026 09:00:03 +0300</pubDate>
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    <itunes:title>Episode 97 - Advanced Topic: AI in Warfare</itunes:title>
    <title>Episode 97 - Advanced Topic: AI in Warfare</title>
    <itunes:summary><![CDATA[In Episode 24 of '100 Days of Data,' Jonas and Amy explore JSON.stringify(), a core JavaScript function that converts complex data structures into JSON-formatted strings. This process, known as serialization, enables seamless data exchange between systems, making data portable and easy to transmit. They discuss its practical applications across industries, from connected vehicle data streaming to secure healthcare communications, highlighting how customization options help balance efficiency ...]]></itunes:summary>
    <description><![CDATA[In Episode 24 of &apos;100 Days of Data,&apos; Jonas and Amy explore JSON.stringify(), a core JavaScript function that converts complex data structures into JSON-formatted strings. This process, known as serialization, enables seamless data exchange between systems, making data portable and easy to transmit. They discuss its practical applications across industries, from connected vehicle data streaming to secure healthcare communications, highlighting how customization options help balance efficiency and privacy. The conversation also covers common pitfalls, such as handling circular references and limitations like the exclusion of functions during serialization. Ultimately, the episode reveals how JSON.stringify() underpins interoperability in today’s AI and digital ecosystems, empowering businesses to optimize their data workflows and maintain security while scaling operations.]]></description>
    <content:encoded><![CDATA[In Episode 24 of &apos;100 Days of Data,&apos; Jonas and Amy explore JSON.stringify(), a core JavaScript function that converts complex data structures into JSON-formatted strings. This process, known as serialization, enables seamless data exchange between systems, making data portable and easy to transmit. They discuss its practical applications across industries, from connected vehicle data streaming to secure healthcare communications, highlighting how customization options help balance efficiency and privacy. The conversation also covers common pitfalls, such as handling circular references and limitations like the exclusion of functions during serialization. Ultimately, the episode reveals how JSON.stringify() underpins interoperability in today’s AI and digital ecosystems, empowering businesses to optimize their data workflows and maintain security while scaling operations.]]></content:encoded>
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    <pubDate>Mon, 06 Apr 2026 09:00:04 +0300</pubDate>
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    <itunes:duration>387</itunes:duration>
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    <itunes:title>Episode 96 - Advanced Topic: AI Governance</itunes:title>
    <title>Episode 96 - Advanced Topic: AI Governance</title>
    <itunes:summary><![CDATA[In Episode 17 of '100 Days of Data,' Jonas and Amy explore the critical role of JSON.stringify() in AI data handling. This JavaScript method converts complex objects into a standardized JSON string format, enabling seamless data exchange across diverse systems. They discuss real-world examples, such as healthcare and automotive industries, highlighting how proper serialization preserves data integrity and prevents costly errors. The episode also covers the advantages of JSON over other format...]]></itunes:summary>
    <description><![CDATA[In Episode 17 of &apos;100 Days of Data,&apos; Jonas and Amy explore the critical role of JSON.stringify() in AI data handling. This JavaScript method converts complex objects into a standardized JSON string format, enabling seamless data exchange across diverse systems. They discuss real-world examples, such as healthcare and automotive industries, highlighting how proper serialization preserves data integrity and prevents costly errors. The episode also covers the advantages of JSON over other formats like XML and CSV, emphasizing its readability, hierarchical structure, and widespread use in APIs and distributed AI computing. Jonas and Amy further explain serialization challenges, practical tips using replacer functions for data privacy, and why mastering JSON.stringify() is essential for building reliable, efficient AI systems.]]></description>
    <content:encoded><![CDATA[In Episode 17 of &apos;100 Days of Data,&apos; Jonas and Amy explore the critical role of JSON.stringify() in AI data handling. This JavaScript method converts complex objects into a standardized JSON string format, enabling seamless data exchange across diverse systems. They discuss real-world examples, such as healthcare and automotive industries, highlighting how proper serialization preserves data integrity and prevents costly errors. The episode also covers the advantages of JSON over other formats like XML and CSV, emphasizing its readability, hierarchical structure, and widespread use in APIs and distributed AI computing. Jonas and Amy further explain serialization challenges, practical tips using replacer functions for data privacy, and why mastering JSON.stringify() is essential for building reliable, efficient AI systems.]]></content:encoded>
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    <itunes:duration>438</itunes:duration>
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    <itunes:title>Episode 95 - Advanced Topic: Multimodal AI</itunes:title>
    <title>Episode 95 - Advanced Topic: Multimodal AI</title>
    <itunes:summary><![CDATA[In Episode 24 of "100 Days of Data," Jonas and Amy demystify JSON.stringify(), a fundamental function that transforms complex data structures into a readable string format. They explain how this serialization process enables seamless data exchange across different systems, highlighting its importance in real-world applications from retail to healthcare and finance. The hosts discuss practical challenges, such as excluding sensitive data and handling unsupported types like functions, while emp...]]></itunes:summary>
    <description><![CDATA[In Episode 24 of &quot;100 Days of Data,&quot; Jonas and Amy demystify JSON.stringify(), a fundamental function that transforms complex data structures into a readable string format. They explain how this serialization process enables seamless data exchange across different systems, highlighting its importance in real-world applications from retail to healthcare and finance. The hosts discuss practical challenges, such as excluding sensitive data and handling unsupported types like functions, while emphasizing JSON’s advantages—simplicity, readability, and broad compatibility. They also touch on customizing serialization and when alternatives may be necessary. By mastering JSON.stringify(), listeners gain a crucial tool for ensuring data clarity, security, and integration efficiency in AI and business environments.]]></description>
    <content:encoded><![CDATA[In Episode 24 of &quot;100 Days of Data,&quot; Jonas and Amy demystify JSON.stringify(), a fundamental function that transforms complex data structures into a readable string format. They explain how this serialization process enables seamless data exchange across different systems, highlighting its importance in real-world applications from retail to healthcare and finance. The hosts discuss practical challenges, such as excluding sensitive data and handling unsupported types like functions, while emphasizing JSON’s advantages—simplicity, readability, and broad compatibility. They also touch on customizing serialization and when alternatives may be necessary. By mastering JSON.stringify(), listeners gain a crucial tool for ensuring data clarity, security, and integration efficiency in AI and business environments.]]></content:encoded>
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    <itunes:title>Episode 94 - Advanced Topic: Synthetic Data</itunes:title>
    <title>Episode 94 - Advanced Topic: Synthetic Data</title>
    <itunes:summary><![CDATA[In Episode 17 of '100 Days of Data,' Jonas and Amy explore the vital role of the JavaScript function JSON.stringify() in making data portable and interoperable across systems. They explain how this function converts complex data objects into readable JSON strings, enabling smooth data exchange in diverse domains like automotive manufacturing and healthcare. Beyond its technical basics, the hosts discuss JSON.stringify()’s impact on integration speed, data privacy customization, and overcoming...]]></itunes:summary>
    <description><![CDATA[In Episode 17 of &apos;100 Days of Data,&apos; Jonas and Amy explore the vital role of the JavaScript function JSON.stringify() in making data portable and interoperable across systems. They explain how this function converts complex data objects into readable JSON strings, enabling smooth data exchange in diverse domains like automotive manufacturing and healthcare. Beyond its technical basics, the hosts discuss JSON.stringify()’s impact on integration speed, data privacy customization, and overcoming serialization challenges such as circular references. By highlighting how JSON.stringify() supports seamless communication between legacy systems, cloud services, and AI tools, this episode unpacks a foundational concept behind today’s data-driven innovations.]]></description>
    <content:encoded><![CDATA[In Episode 17 of &apos;100 Days of Data,&apos; Jonas and Amy explore the vital role of the JavaScript function JSON.stringify() in making data portable and interoperable across systems. They explain how this function converts complex data objects into readable JSON strings, enabling smooth data exchange in diverse domains like automotive manufacturing and healthcare. Beyond its technical basics, the hosts discuss JSON.stringify()’s impact on integration speed, data privacy customization, and overcoming serialization challenges such as circular references. By highlighting how JSON.stringify() supports seamless communication between legacy systems, cloud services, and AI tools, this episode unpacks a foundational concept behind today’s data-driven innovations.]]></content:encoded>
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    <pubDate>Wed, 01 Apr 2026 09:00:06 +0300</pubDate>
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    <itunes:title>Episode 93 - Advanced Topic: Federated Learning</itunes:title>
    <title>Episode 93 - Advanced Topic: Federated Learning</title>
    <itunes:summary><![CDATA[In Episode 12 of 100 Days of Data, Jonas and Amy dive into JSON.stringify(), a crucial tool that transforms complex data structures into standardized JSON strings. They explain how this lightweight format enables smooth data exchange across systems—powering everything from web APIs to retail analytics. The hosts highlight the importance of serialization for consistent, structured, and secure data communication. They also discuss practical challenges like JSON.stringify()’s limitations with fu...]]></itunes:summary>
    <description><![CDATA[In Episode 12 of 100 Days of Data, Jonas and Amy dive into JSON.stringify(), a crucial tool that transforms complex data structures into standardized JSON strings. They explain how this lightweight format enables smooth data exchange across systems—powering everything from web APIs to retail analytics. The hosts highlight the importance of serialization for consistent, structured, and secure data communication. They also discuss practical challenges like JSON.stringify()’s limitations with functions and date objects, emphasizing the need for careful data design. By understanding JSON.stringify(), listeners will gain insight into how data moves and lives in today’s digital world, setting the stage for confident handling of data serialization in AI and business contexts.]]></description>
    <content:encoded><![CDATA[In Episode 12 of 100 Days of Data, Jonas and Amy dive into JSON.stringify(), a crucial tool that transforms complex data structures into standardized JSON strings. They explain how this lightweight format enables smooth data exchange across systems—powering everything from web APIs to retail analytics. The hosts highlight the importance of serialization for consistent, structured, and secure data communication. They also discuss practical challenges like JSON.stringify()’s limitations with functions and date objects, emphasizing the need for careful data design. By understanding JSON.stringify(), listeners will gain insight into how data moves and lives in today’s digital world, setting the stage for confident handling of data serialization in AI and business contexts.]]></content:encoded>
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    <pubDate>Tue, 31 Mar 2026 09:00:05 +0300</pubDate>
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    <itunes:title>Episode 92 - Advanced Topic: Edge AI</itunes:title>
    <title>Episode 92 - Advanced Topic: Edge AI</title>
    <itunes:summary><![CDATA[In Episode 24 of "100 Days of Data," Jonas and Amy explore the vital JavaScript method JSON.stringify(), which converts complex data structures into JSON-formatted strings for efficient sharing and storage. They discuss how this simple yet powerful function enables smooth data transfer across AI systems and businesses by serializing objects and arrays into text. The hosts highlight practical use cases, such as e-commerce transactions and secure financial data sharing, while also addressing co...]]></itunes:summary>
    <description><![CDATA[In Episode 24 of &quot;100 Days of Data,&quot; Jonas and Amy explore the vital JavaScript method JSON.stringify(), which converts complex data structures into JSON-formatted strings for efficient sharing and storage. They discuss how this simple yet powerful function enables smooth data transfer across AI systems and businesses by serializing objects and arrays into text. The hosts highlight practical use cases, such as e-commerce transactions and secure financial data sharing, while also addressing common serialization challenges like handling dates, functions, and special values. Amy and Jonas emphasize the importance of understanding JSON.stringify()’s parameters, like replacers and spacing, to tailor serialization effectively. Overall, this episode illuminates the often-overlooked but essential role JSON.stringify() plays in powering AI workflows and ensuring data integrity in distributed environments.]]></description>
    <content:encoded><![CDATA[In Episode 24 of &quot;100 Days of Data,&quot; Jonas and Amy explore the vital JavaScript method JSON.stringify(), which converts complex data structures into JSON-formatted strings for efficient sharing and storage. They discuss how this simple yet powerful function enables smooth data transfer across AI systems and businesses by serializing objects and arrays into text. The hosts highlight practical use cases, such as e-commerce transactions and secure financial data sharing, while also addressing common serialization challenges like handling dates, functions, and special values. Amy and Jonas emphasize the importance of understanding JSON.stringify()’s parameters, like replacers and spacing, to tailor serialization effectively. Overall, this episode illuminates the often-overlooked but essential role JSON.stringify() plays in powering AI workflows and ensuring data integrity in distributed environments.]]></content:encoded>
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    <pubDate>Mon, 30 Mar 2026 09:00:07 +0300</pubDate>
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    <itunes:title>Episode 91 - Checkpoint: Case Studies</itunes:title>
    <title>Episode 91 - Checkpoint: Case Studies</title>
    <itunes:summary><![CDATA[In Episode 91 of '100 Days of Data,' Jonas and Amy reflect on the crucial role of JSON and the JSON.stringify() function in AI and business data exchange. They explore how JSON’s lightweight, standardized format transforms complex data structures into readable, interoperable text strings, enabling seamless communication between apps, devices, and AI systems. Through engaging case studies—from healthcare monitoring to banking privacy and logistics tracking—they reveal how mastering JSON serial...]]></itunes:summary>
    <description><![CDATA[In Episode 91 of &apos;100 Days of Data,&apos; Jonas and Amy reflect on the crucial role of JSON and the JSON.stringify() function in AI and business data exchange. They explore how JSON’s lightweight, standardized format transforms complex data structures into readable, interoperable text strings, enabling seamless communication between apps, devices, and AI systems. Through engaging case studies—from healthcare monitoring to banking privacy and logistics tracking—they reveal how mastering JSON serialization enhances data security, efficiency, and collaboration across corporate teams. The hosts also discuss practical considerations like handling circular references and customizing data output to protect sensitive information. Ultimately, this episode emphasizes reflection on proven data practices and how these learnings from the giants of tech can boost AI adoption and drive faster business outcomes.]]></description>
    <content:encoded><![CDATA[In Episode 91 of &apos;100 Days of Data,&apos; Jonas and Amy reflect on the crucial role of JSON and the JSON.stringify() function in AI and business data exchange. They explore how JSON’s lightweight, standardized format transforms complex data structures into readable, interoperable text strings, enabling seamless communication between apps, devices, and AI systems. Through engaging case studies—from healthcare monitoring to banking privacy and logistics tracking—they reveal how mastering JSON serialization enhances data security, efficiency, and collaboration across corporate teams. The hosts also discuss practical considerations like handling circular references and customizing data output to protect sensitive information. Ultimately, this episode emphasizes reflection on proven data practices and how these learnings from the giants of tech can boost AI adoption and drive faster business outcomes.]]></content:encoded>
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    <pubDate>Fri, 27 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>482</itunes:duration>
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    <itunes:title>Episode 90 - Case Study: Meta</itunes:title>
    <title>Episode 90 - Case Study: Meta</title>
    <itunes:summary><![CDATA[In this episode of 100 Days of Data, Jonas and Amy explore the vital role of the JSON.stringify() method in AI and data workflows. They explain how this JavaScript function converts complex data objects into JSON strings, enabling seamless data exchange between applications, servers, and storage. From practical examples in finance and automotive industries to challenges like handling non-serializable data types, the hosts uncover how JSON.stringify() preserves data integrity, supports debuggi...]]></itunes:summary>
    <description><![CDATA[In this episode of 100 Days of Data, Jonas and Amy explore the vital role of the JSON.stringify() method in AI and data workflows. They explain how this JavaScript function converts complex data objects into JSON strings, enabling seamless data exchange between applications, servers, and storage. From practical examples in finance and automotive industries to challenges like handling non-serializable data types, the hosts uncover how JSON.stringify() preserves data integrity, supports debugging, and optimizes performance. They also discuss customization features and best practices for managing serialized data at scale. Ultimately, this episode highlights how mastering JSON.stringify() strengthens data pipelines and improves the reliability of AI projects across industries.]]></description>
    <content:encoded><![CDATA[In this episode of 100 Days of Data, Jonas and Amy explore the vital role of the JSON.stringify() method in AI and data workflows. They explain how this JavaScript function converts complex data objects into JSON strings, enabling seamless data exchange between applications, servers, and storage. From practical examples in finance and automotive industries to challenges like handling non-serializable data types, the hosts uncover how JSON.stringify() preserves data integrity, supports debugging, and optimizes performance. They also discuss customization features and best practices for managing serialized data at scale. Ultimately, this episode highlights how mastering JSON.stringify() strengthens data pipelines and improves the reliability of AI projects across industries.]]></content:encoded>
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    <pubDate>Thu, 26 Mar 2026 18:06:54 +0200</pubDate>
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    <itunes:duration>460</itunes:duration>
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    <itunes:title>Episode 89 - Case Study: Nvidia</itunes:title>
    <title>Episode 89 - Case Study: Nvidia</title>
    <itunes:summary><![CDATA[In Episode 89 of ‘100 Days of Data,’ Jonas and Amy explore Nvidia’s remarkable transformation from a graphics chipmaker to a driving force in AI technology. They explain how Nvidia’s GPUs—originally designed for rendering video game graphics—became essential for AI due to their parallel processing power. The hosts highlight Nvidia’s innovation in AI-specific hardware like Tensor Cores and their comprehensive software ecosystem, including CUDA and DGX systems. These advancements have accelerat...]]></itunes:summary>
    <description><![CDATA[In Episode 89 of ‘100 Days of Data,’ Jonas and Amy explore Nvidia’s remarkable transformation from a graphics chipmaker to a driving force in AI technology. They explain how Nvidia’s GPUs—originally designed for rendering video game graphics—became essential for AI due to their parallel processing power. The hosts highlight Nvidia’s innovation in AI-specific hardware like Tensor Cores and their comprehensive software ecosystem, including CUDA and DGX systems. These advancements have accelerated AI research and scaled AI applications across industries such as healthcare, automotive, and finance. The episode underscores how integrating specialized hardware with software enables breakthrough AI performance and how Nvidia’s strategic agility exemplifies navigating the rapidly evolving AI landscape.]]></description>
    <content:encoded><![CDATA[In Episode 89 of ‘100 Days of Data,’ Jonas and Amy explore Nvidia’s remarkable transformation from a graphics chipmaker to a driving force in AI technology. They explain how Nvidia’s GPUs—originally designed for rendering video game graphics—became essential for AI due to their parallel processing power. The hosts highlight Nvidia’s innovation in AI-specific hardware like Tensor Cores and their comprehensive software ecosystem, including CUDA and DGX systems. These advancements have accelerated AI research and scaled AI applications across industries such as healthcare, automotive, and finance. The episode underscores how integrating specialized hardware with software enables breakthrough AI performance and how Nvidia’s strategic agility exemplifies navigating the rapidly evolving AI landscape.]]></content:encoded>
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    <pubDate>Wed, 25 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>412</itunes:duration>
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  <item>
    <itunes:title>Episode 88 - Case Study: Apple</itunes:title>
    <title>Episode 88 - Case Study: Apple</title>
    <itunes:summary><![CDATA[In Episode 88 of '100 Days of Data,' Jonas and Amy explore Apple's unique approach to AI, highlighting how the company embeds intelligence directly into its hardware to create seamless, user-centric experiences. They discuss Siri’s evolution from cloud-heavy processing to on-device AI powered by Apple’s custom Neural Engine, emphasizing privacy, speed, and efficiency. The hosts explain how Apple’s integration of AI with hardware enables personalized services—like face recognition and health m...]]></itunes:summary>
    <description><![CDATA[In Episode 88 of &apos;100 Days of Data,&apos; Jonas and Amy explore Apple&apos;s unique approach to AI, highlighting how the company embeds intelligence directly into its hardware to create seamless, user-centric experiences. They discuss Siri’s evolution from cloud-heavy processing to on-device AI powered by Apple’s custom Neural Engine, emphasizing privacy, speed, and efficiency. The hosts explain how Apple’s integration of AI with hardware enables personalized services—like face recognition and health monitoring—while keeping user data private. By focusing on invisible AI that simplifies daily interactions, Apple delivers technology that feels effortless yet powerful. This episode also addresses the trade-offs Apple makes in balancing innovation, privacy, and ecosystem control, offering insights relevant to businesses looking to harness AI with a user-first mindset.]]></description>
    <content:encoded><![CDATA[In Episode 88 of &apos;100 Days of Data,&apos; Jonas and Amy explore Apple&apos;s unique approach to AI, highlighting how the company embeds intelligence directly into its hardware to create seamless, user-centric experiences. They discuss Siri’s evolution from cloud-heavy processing to on-device AI powered by Apple’s custom Neural Engine, emphasizing privacy, speed, and efficiency. The hosts explain how Apple’s integration of AI with hardware enables personalized services—like face recognition and health monitoring—while keeping user data private. By focusing on invisible AI that simplifies daily interactions, Apple delivers technology that feels effortless yet powerful. This episode also addresses the trade-offs Apple makes in balancing innovation, privacy, and ecosystem control, offering insights relevant to businesses looking to harness AI with a user-first mindset.]]></content:encoded>
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    <pubDate>Tue, 24 Mar 2026 09:00:05 +0200</pubDate>
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    <itunes:duration>492</itunes:duration>
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  <item>
    <itunes:title>Episode 87 - Case Study: Baidu &amp; China</itunes:title>
    <title>Episode 87 - Case Study: Baidu &amp; China</title>
    <itunes:summary><![CDATA[In Episode 87 of 100 Days of Data, Jonas and Amy explore China’s national AI strategy through the lens of Baidu, one of its leading tech giants. They examine how China’s government-driven, long-term approach aligns public policy, research, and industry to accelerate AI development. Baidu’s transformation from a search engine to an AI powerhouse highlights advances in natural language processing, autonomous driving, and healthcare AI. The hosts emphasize the unique advantages of China’s data e...]]></itunes:summary>
    <description><![CDATA[In Episode 87 of 100 Days of Data, Jonas and Amy explore China’s national AI strategy through the lens of Baidu, one of its leading tech giants. They examine how China’s government-driven, long-term approach aligns public policy, research, and industry to accelerate AI development. Baidu’s transformation from a search engine to an AI powerhouse highlights advances in natural language processing, autonomous driving, and healthcare AI. The hosts emphasize the unique advantages of China’s data environment and its ecosystem that combines academia, industry, and government support. Challenges like regulatory hurdles and infrastructure integration are also discussed, illustrating the complex realities of scaling AI nationally. This episode offers valuable insights into the power of coordinated AI strategy and the broader impact of AI beyond commercial uses toward societal benefits.]]></description>
    <content:encoded><![CDATA[In Episode 87 of 100 Days of Data, Jonas and Amy explore China’s national AI strategy through the lens of Baidu, one of its leading tech giants. They examine how China’s government-driven, long-term approach aligns public policy, research, and industry to accelerate AI development. Baidu’s transformation from a search engine to an AI powerhouse highlights advances in natural language processing, autonomous driving, and healthcare AI. The hosts emphasize the unique advantages of China’s data environment and its ecosystem that combines academia, industry, and government support. Challenges like regulatory hurdles and infrastructure integration are also discussed, illustrating the complex realities of scaling AI nationally. This episode offers valuable insights into the power of coordinated AI strategy and the broader impact of AI beyond commercial uses toward societal benefits.]]></content:encoded>
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    <pubDate>Mon, 23 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>360</itunes:duration>
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    <itunes:title>Episode 86 - Case Study: OpenAI</itunes:title>
    <title>Episode 86 - Case Study: OpenAI</title>
    <itunes:summary><![CDATA[In Episode 86 of "100 Days of Data," Jonas and Amy dive into OpenAI’s transformative role in generative AI, focusing on the breakthroughs of GPT and DALL·E. They explain how large language models (LLMs) like GPT use the innovative transformer architecture to understand and generate human language, enabling applications from chatbots to automated content creation. The episode highlights OpenAI’s training process, including pre-training and fine-tuning, and its emphasis on safety through techni...]]></itunes:summary>
    <description><![CDATA[In Episode 86 of &quot;100 Days of Data,&quot; Jonas and Amy dive into OpenAI’s transformative role in generative AI, focusing on the breakthroughs of GPT and DALL·E. They explain how large language models (LLMs) like GPT use the innovative transformer architecture to understand and generate human language, enabling applications from chatbots to automated content creation. The episode highlights OpenAI’s training process, including pre-training and fine-tuning, and its emphasis on safety through techniques like reinforcement learning from human feedback. Amy shares practical examples of GPT’s impact across industries, such as healthcare and retail, while Jonas discusses DALL·E’s image generation capabilities. Together, they emphasize how generative AI is revolutionizing creativity, customer experiences, and business workflows—all while stressing the need for ethical deployment and human collaboration in this rapidly evolving field.]]></description>
    <content:encoded><![CDATA[In Episode 86 of &quot;100 Days of Data,&quot; Jonas and Amy dive into OpenAI’s transformative role in generative AI, focusing on the breakthroughs of GPT and DALL·E. They explain how large language models (LLMs) like GPT use the innovative transformer architecture to understand and generate human language, enabling applications from chatbots to automated content creation. The episode highlights OpenAI’s training process, including pre-training and fine-tuning, and its emphasis on safety through techniques like reinforcement learning from human feedback. Amy shares practical examples of GPT’s impact across industries, such as healthcare and retail, while Jonas discusses DALL·E’s image generation capabilities. Together, they emphasize how generative AI is revolutionizing creativity, customer experiences, and business workflows—all while stressing the need for ethical deployment and human collaboration in this rapidly evolving field.]]></content:encoded>
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    <pubDate>Fri, 20 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>453</itunes:duration>
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  <item>
    <itunes:title>Episode 85 - Case Study: Microsoft</itunes:title>
    <title>Episode 85 - Case Study: Microsoft</title>
    <itunes:summary><![CDATA[In Episode 85 of 100 Days of Data, Jonas and Amy explore Microsoft’s transformative use of AI copilots that enhance productivity across industries. From everyday tools like Word and Excel to developer-focused solutions such as GitHub Copilot, Microsoft leverages cloud computing, machine learning, and vast data ecosystems to create intelligent assistants that work seamlessly alongside humans. The hosts discuss how Microsoft’s Azure platform supports real-time AI interactions while maintaining ...]]></itunes:summary>
    <description><![CDATA[In Episode 85 of 100 Days of Data, Jonas and Amy explore Microsoft’s transformative use of AI copilots that enhance productivity across industries. From everyday tools like Word and Excel to developer-focused solutions such as GitHub Copilot, Microsoft leverages cloud computing, machine learning, and vast data ecosystems to create intelligent assistants that work seamlessly alongside humans. The hosts discuss how Microsoft’s Azure platform supports real-time AI interactions while maintaining strong data privacy and governance. Practical case studies highlight efficiency gains in sectors like automotive, finance, retail, and healthcare. Emphasizing the human-in-the-loop approach, they note that AI copilots augment human effort without replacing judgment, driving smarter workflows and collaboration. This episode offers an insightful deep dive into the technology, business impact, and ethical considerations that make Microsoft a leader in embedding AI into everyday work.]]></description>
    <content:encoded><![CDATA[In Episode 85 of 100 Days of Data, Jonas and Amy explore Microsoft’s transformative use of AI copilots that enhance productivity across industries. From everyday tools like Word and Excel to developer-focused solutions such as GitHub Copilot, Microsoft leverages cloud computing, machine learning, and vast data ecosystems to create intelligent assistants that work seamlessly alongside humans. The hosts discuss how Microsoft’s Azure platform supports real-time AI interactions while maintaining strong data privacy and governance. Practical case studies highlight efficiency gains in sectors like automotive, finance, retail, and healthcare. Emphasizing the human-in-the-loop approach, they note that AI copilots augment human effort without replacing judgment, driving smarter workflows and collaboration. This episode offers an insightful deep dive into the technology, business impact, and ethical considerations that make Microsoft a leader in embedding AI into everyday work.]]></content:encoded>
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    <pubDate>Thu, 19 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>505</itunes:duration>
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  <item>
    <itunes:title>Episode 84 - Case Study: Amazon</itunes:title>
    <title>Episode 84 - Case Study: Amazon</title>
    <itunes:summary><![CDATA[In Episode 84 of 100 Days of Data, Jonas and Amy explore how Amazon harnesses AI to transform logistics, retail, and everyday life through Alexa. They dive into Amazon’s recommendation engine, powered by collaborative filtering and machine learning, which drives 35% of its revenue by personalizing customer experiences. The hosts also highlight AI’s critical role in optimizing Amazon’s complex fulfillment centers and last-mile delivery routes using robotics and real-time data. Additionally, th...]]></itunes:summary>
    <description><![CDATA[In Episode 84 of 100 Days of Data, Jonas and Amy explore how Amazon harnesses AI to transform logistics, retail, and everyday life through Alexa. They dive into Amazon’s recommendation engine, powered by collaborative filtering and machine learning, which drives 35% of its revenue by personalizing customer experiences. The hosts also highlight AI’s critical role in optimizing Amazon’s complex fulfillment centers and last-mile delivery routes using robotics and real-time data. Additionally, they discuss Alexa’s advanced natural language processing capabilities that enable seamless voice interactions. Alongside the impressive innovations, Jonas and Amy touch on ethical challenges such as privacy, bias, and data security, emphasizing Amazon’s ongoing commitment to responsible AI. This episode offers a comprehensive look at how Amazon integrates AI deeply into its business operations, providing valuable lessons on leveraging data and AI strategies for both customer experience and operational excellence.]]></description>
    <content:encoded><![CDATA[In Episode 84 of 100 Days of Data, Jonas and Amy explore how Amazon harnesses AI to transform logistics, retail, and everyday life through Alexa. They dive into Amazon’s recommendation engine, powered by collaborative filtering and machine learning, which drives 35% of its revenue by personalizing customer experiences. The hosts also highlight AI’s critical role in optimizing Amazon’s complex fulfillment centers and last-mile delivery routes using robotics and real-time data. Additionally, they discuss Alexa’s advanced natural language processing capabilities that enable seamless voice interactions. Alongside the impressive innovations, Jonas and Amy touch on ethical challenges such as privacy, bias, and data security, emphasizing Amazon’s ongoing commitment to responsible AI. This episode offers a comprehensive look at how Amazon integrates AI deeply into its business operations, providing valuable lessons on leveraging data and AI strategies for both customer experience and operational excellence.]]></content:encoded>
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    <pubDate>Wed, 18 Mar 2026 09:00:03 +0200</pubDate>
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    <itunes:duration>417</itunes:duration>
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    <itunes:title>Episode 83 - Case Study: Google</itunes:title>
    <title>Episode 83 - Case Study: Google</title>
    <itunes:summary><![CDATA[In Episode 83 of '100 Days of Data,' Jonas and Amy explore how Google leverages massive amounts of data and advanced AI to power its search engine, advertising platform, and cloud services. They delve into the evolution from the original PageRank algorithm to modern natural language processing models like BERT and MUM, illustrating how AI improves user experience and business outcomes. The episode highlights Google's expertly engineered infrastructure that manages billions of daily searches a...]]></itunes:summary>
    <description><![CDATA[In Episode 83 of &apos;100 Days of Data,&apos; Jonas and Amy explore how Google leverages massive amounts of data and advanced AI to power its search engine, advertising platform, and cloud services. They delve into the evolution from the original PageRank algorithm to modern natural language processing models like BERT and MUM, illustrating how AI improves user experience and business outcomes. The episode highlights Google&apos;s expertly engineered infrastructure that manages billions of daily searches and ad requests while addressing privacy and ethical considerations. From targeted ad auctions to scalable cloud AI services, listeners gain insight into how Google’s data-driven ecosystem drives innovation and accessibility across industries.]]></description>
    <content:encoded><![CDATA[In Episode 83 of &apos;100 Days of Data,&apos; Jonas and Amy explore how Google leverages massive amounts of data and advanced AI to power its search engine, advertising platform, and cloud services. They delve into the evolution from the original PageRank algorithm to modern natural language processing models like BERT and MUM, illustrating how AI improves user experience and business outcomes. The episode highlights Google&apos;s expertly engineered infrastructure that manages billions of daily searches and ad requests while addressing privacy and ethical considerations. From targeted ad auctions to scalable cloud AI services, listeners gain insight into how Google’s data-driven ecosystem drives innovation and accessibility across industries.]]></content:encoded>
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    <pubDate>Tue, 17 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>364</itunes:duration>
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    <itunes:title>Episode 82 - Case Study: Tesla</itunes:title>
    <title>Episode 82 - Case Study: Tesla</title>
    <itunes:summary><![CDATA[In Episode 82 of "100 Days of Data," Jonas and Amy explore Tesla’s groundbreaking use of AI to transform autonomous driving and mobility. They delve into Tesla's data-driven approach, emphasizing vision-based AI over costly LiDAR systems, and how vast amounts of real-world driving data power continuous learning. The episode highlights Tesla’s innovative feedback loops, combining supervised and reinforcement learning to improve decision-making and handle rare edge cases through fleet-wide data...]]></itunes:summary>
    <description><![CDATA[In Episode 82 of &quot;100 Days of Data,&quot; Jonas and Amy explore Tesla’s groundbreaking use of AI to transform autonomous driving and mobility. They delve into Tesla&apos;s data-driven approach, emphasizing vision-based AI over costly LiDAR systems, and how vast amounts of real-world driving data power continuous learning. The episode highlights Tesla’s innovative feedback loops, combining supervised and reinforcement learning to improve decision-making and handle rare edge cases through fleet-wide data sharing. Beyond technology, Jonas and Amy discuss regulatory challenges, safety concerns, and the strategic role of scalable software updates in evolving Tesla vehicles like smartphones. This case study showcases how AI theory, data strategy, and engineering intersect to drive innovation—offering valuable lessons for businesses aiming to turn data into competitive advantage in complex, real-world applications.]]></description>
    <content:encoded><![CDATA[In Episode 82 of &quot;100 Days of Data,&quot; Jonas and Amy explore Tesla’s groundbreaking use of AI to transform autonomous driving and mobility. They delve into Tesla&apos;s data-driven approach, emphasizing vision-based AI over costly LiDAR systems, and how vast amounts of real-world driving data power continuous learning. The episode highlights Tesla’s innovative feedback loops, combining supervised and reinforcement learning to improve decision-making and handle rare edge cases through fleet-wide data sharing. Beyond technology, Jonas and Amy discuss regulatory challenges, safety concerns, and the strategic role of scalable software updates in evolving Tesla vehicles like smartphones. This case study showcases how AI theory, data strategy, and engineering intersect to drive innovation—offering valuable lessons for businesses aiming to turn data into competitive advantage in complex, real-world applications.]]></content:encoded>
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    <pubDate>Mon, 16 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>452</itunes:duration>
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    <itunes:episode>82</itunes:episode>
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  <item>
    <itunes:title>Episode 81 - Checkpoint: AI People</itunes:title>
    <title>Episode 81 - Checkpoint: AI People</title>
    <itunes:summary><![CDATA[In Episode 81 of '100 Days of Data,' Jonas and Amy reflect on the vital human influence behind artificial intelligence. They explore the pioneers—like Alan Turing and John McCarthy—whose ideas laid the groundwork for today’s AI innovations. Emphasizing that AI is more than algorithms, they highlight the importance of understanding the people who design, build, and use AI systems. The hosts discuss how ethical considerations, bias, and collaboration shape AI’s impact on society and business. T...]]></itunes:summary>
    <description><![CDATA[In Episode 81 of &apos;100 Days of Data,&apos; Jonas and Amy reflect on the vital human influence behind artificial intelligence. They explore the pioneers—like Alan Turing and John McCarthy—whose ideas laid the groundwork for today’s AI innovations. Emphasizing that AI is more than algorithms, they highlight the importance of understanding the people who design, build, and use AI systems. The hosts discuss how ethical considerations, bias, and collaboration shape AI’s impact on society and business. This episode serves as a reminder that behind every AI system are individuals whose values and decisions affect outcomes, making reflection on their influence essential for responsible AI development.]]></description>
    <content:encoded><![CDATA[In Episode 81 of &apos;100 Days of Data,&apos; Jonas and Amy reflect on the vital human influence behind artificial intelligence. They explore the pioneers—like Alan Turing and John McCarthy—whose ideas laid the groundwork for today’s AI innovations. Emphasizing that AI is more than algorithms, they highlight the importance of understanding the people who design, build, and use AI systems. The hosts discuss how ethical considerations, bias, and collaboration shape AI’s impact on society and business. This episode serves as a reminder that behind every AI system are individuals whose values and decisions affect outcomes, making reflection on their influence essential for responsible AI development.]]></content:encoded>
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    <pubDate>Fri, 13 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>351</itunes:duration>
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  <item>
    <itunes:title>Episode 80 - People: Sam Altman</itunes:title>
    <title>Episode 80 - People: Sam Altman</title>
    <itunes:summary><![CDATA[In Episode 80 of '100 Days of Data,' Jonas and Amy explore the influential role of Sam Altman, CEO of OpenAI, in shaping the landscape of generative AI. They discuss Altman’s journey from tech entrepreneur to a visionary leader in artificial intelligence and the business strategies behind OpenAI's rise. The episode delves into how Altman balances innovation, ethics, and commercialization through initiatives like ChatGPT and partnerships with giants like Microsoft. It also highlights his impac...]]></itunes:summary>
    <description><![CDATA[In Episode 80 of &apos;100 Days of Data,&apos; Jonas and Amy explore the influential role of Sam Altman, CEO of OpenAI, in shaping the landscape of generative AI. They discuss Altman’s journey from tech entrepreneur to a visionary leader in artificial intelligence and the business strategies behind OpenAI&apos;s rise. The episode delves into how Altman balances innovation, ethics, and commercialization through initiatives like ChatGPT and partnerships with giants like Microsoft. It also highlights his impact on the broader tech ecosystem through Y Combinator and his skill in making complex AI concepts accessible to business leaders. The hosts underscore the importance of leadership in AI—not just from a technical standpoint, but through communication, governance, and cross-sector collaborations that make AI practical and trusted across industries.]]></description>
    <content:encoded><![CDATA[In Episode 80 of &apos;100 Days of Data,&apos; Jonas and Amy explore the influential role of Sam Altman, CEO of OpenAI, in shaping the landscape of generative AI. They discuss Altman’s journey from tech entrepreneur to a visionary leader in artificial intelligence and the business strategies behind OpenAI&apos;s rise. The episode delves into how Altman balances innovation, ethics, and commercialization through initiatives like ChatGPT and partnerships with giants like Microsoft. It also highlights his impact on the broader tech ecosystem through Y Combinator and his skill in making complex AI concepts accessible to business leaders. The hosts underscore the importance of leadership in AI—not just from a technical standpoint, but through communication, governance, and cross-sector collaborations that make AI practical and trusted across industries.]]></content:encoded>
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    <pubDate>Thu, 12 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>458</itunes:duration>
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  <item>
    <itunes:title>Episode 79 - People: Demis Hassabis</itunes:title>
    <title>Episode 79 - People: Demis Hassabis</title>
    <itunes:summary><![CDATA[In Episode 79 of '100 Days of Data', Jonas and Amy spotlight Demis Hassabis, the visionary behind DeepMind and the revolutionary AlphaGo AI. They explore how Hassabis’s diverse background—from chess prodigy to neuroscientist—informed groundbreaking work in reinforcement learning. The episode unpacks AlphaGo’s historic victory over a world Go champion and discusses the implications of reinforcement learning for both academia and industry. From robotics to healthcare, Jonas and Amy illustrate h...]]></itunes:summary>
    <description><![CDATA[In Episode 79 of &apos;100 Days of Data&apos;, Jonas and Amy spotlight Demis Hassabis, the visionary behind DeepMind and the revolutionary AlphaGo AI. They explore how Hassabis’s diverse background—from chess prodigy to neuroscientist—informed groundbreaking work in reinforcement learning. The episode unpacks AlphaGo’s historic victory over a world Go champion and discusses the implications of reinforcement learning for both academia and industry. From robotics to healthcare, Jonas and Amy illustrate how these AI innovations are reshaping real-world applications. Listeners also gain insight into the fusion of neuroscience and AI, and how DeepMind’s ethos balances scientific openness with enterprise innovation.]]></description>
    <content:encoded><![CDATA[In Episode 79 of &apos;100 Days of Data&apos;, Jonas and Amy spotlight Demis Hassabis, the visionary behind DeepMind and the revolutionary AlphaGo AI. They explore how Hassabis’s diverse background—from chess prodigy to neuroscientist—informed groundbreaking work in reinforcement learning. The episode unpacks AlphaGo’s historic victory over a world Go champion and discusses the implications of reinforcement learning for both academia and industry. From robotics to healthcare, Jonas and Amy illustrate how these AI innovations are reshaping real-world applications. Listeners also gain insight into the fusion of neuroscience and AI, and how DeepMind’s ethos balances scientific openness with enterprise innovation.]]></content:encoded>
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    <pubDate>Wed, 11 Mar 2026 09:00:03 +0200</pubDate>
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    <itunes:duration>405</itunes:duration>
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  <item>
    <itunes:title>Episode 78 - People: Yann LeCun</itunes:title>
    <title>Episode 78 - People: Yann LeCun</title>
    <itunes:summary><![CDATA[In Episode 78 of '100 Days of Data,' Jonas and Amy spotlight the pioneering work of Yann LeCun, one of the key architects of modern deep learning. From his early development of convolutional neural networks (CNNs) to his leadership at Meta (formerly Facebook) as Chief AI Scientist, LeCun’s career bridges academic innovation and industrial application. The hosts explore how CNNs revolutionized image recognition and enabled AI to better interpret visual data — a foundation now used across indus...]]></itunes:summary>
    <description><![CDATA[In Episode 78 of &apos;100 Days of Data,&apos; Jonas and Amy spotlight the pioneering work of Yann LeCun, one of the key architects of modern deep learning. From his early development of convolutional neural networks (CNNs) to his leadership at Meta (formerly Facebook) as Chief AI Scientist, LeCun’s career bridges academic innovation and industrial application. The hosts explore how CNNs revolutionized image recognition and enabled AI to better interpret visual data — a foundation now used across industries like healthcare, finance, and autonomous vehicles. They also discuss LeCun’s broader contributions, including work on energy-based models and reinforcement learning, highlighting the practical impact of his theoretical insights. This episode showcases how solid AI foundations and scalable models have transformed real-world applications for billions.]]></description>
    <content:encoded><![CDATA[In Episode 78 of &apos;100 Days of Data,&apos; Jonas and Amy spotlight the pioneering work of Yann LeCun, one of the key architects of modern deep learning. From his early development of convolutional neural networks (CNNs) to his leadership at Meta (formerly Facebook) as Chief AI Scientist, LeCun’s career bridges academic innovation and industrial application. The hosts explore how CNNs revolutionized image recognition and enabled AI to better interpret visual data — a foundation now used across industries like healthcare, finance, and autonomous vehicles. They also discuss LeCun’s broader contributions, including work on energy-based models and reinforcement learning, highlighting the practical impact of his theoretical insights. This episode showcases how solid AI foundations and scalable models have transformed real-world applications for billions.]]></content:encoded>
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    <pubDate>Tue, 10 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:duration>437</itunes:duration>
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    <itunes:title>Episode 77 - People: Fei-Fei Li</itunes:title>
    <title>Episode 77 - People: Fei-Fei Li</title>
    <itunes:summary><![CDATA[In Episode 77 of '100 Days of Data,' hosts Jonas and Amy take a deep dive into the groundbreaking work of Fei-Fei Li, the creator of ImageNet and a transformative figure in computer vision. They explore how her insight into the importance of large-scale, labeled datasets fueled the deep learning revolution and enabled machines to 'see' with unprecedented accuracy. From the technical design of ImageNet’s 14 million-tagged images to the sweeping impact her work has had across industries like he...]]></itunes:summary>
    <description><![CDATA[In Episode 77 of &apos;100 Days of Data,&apos; hosts Jonas and Amy take a deep dive into the groundbreaking work of Fei-Fei Li, the creator of ImageNet and a transformative figure in computer vision. They explore how her insight into the importance of large-scale, labeled datasets fueled the deep learning revolution and enabled machines to &apos;see&apos; with unprecedented accuracy. From the technical design of ImageNet’s 14 million-tagged images to the sweeping impact her work has had across industries like healthcare and autonomous vehicles, this episode highlights how foundational data truly is in AI development. The conversation also weaves in the ethical responsibilities that come with curating such datasets, as well as Fei-Fei Li’s broader mission to diversify and democratize AI. This episode offers both inspiration and practical insight into why visionary data work matters.]]></description>
    <content:encoded><![CDATA[In Episode 77 of &apos;100 Days of Data,&apos; hosts Jonas and Amy take a deep dive into the groundbreaking work of Fei-Fei Li, the creator of ImageNet and a transformative figure in computer vision. They explore how her insight into the importance of large-scale, labeled datasets fueled the deep learning revolution and enabled machines to &apos;see&apos; with unprecedented accuracy. From the technical design of ImageNet’s 14 million-tagged images to the sweeping impact her work has had across industries like healthcare and autonomous vehicles, this episode highlights how foundational data truly is in AI development. The conversation also weaves in the ethical responsibilities that come with curating such datasets, as well as Fei-Fei Li’s broader mission to diversify and democratize AI. This episode offers both inspiration and practical insight into why visionary data work matters.]]></content:encoded>
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    <pubDate>Mon, 09 Mar 2026 09:00:05 +0200</pubDate>
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    <itunes:title>Episode 76 - People: Andrew Ng</itunes:title>
    <title>Episode 76 - People: Andrew Ng</title>
    <itunes:summary><![CDATA[In Episode 76 of '100 Days of Data,' Jonas and Amy spotlight Andrew Ng, the MOOC pioneer who transformed AI education by making it accessible online. As a Stanford professor and co-founder of Coursera, Ng revolutionized how machine learning is taught, empowering millions globally with high-quality, scalable learning resources. The hosts explore his approachable teaching methods, the rise of MOOCs, and the long-term impact on industry and global talent pipelines. From foundational concepts lik...]]></itunes:summary>
    <description><![CDATA[In Episode 76 of &apos;100 Days of Data,&apos; Jonas and Amy spotlight Andrew Ng, the MOOC pioneer who transformed AI education by making it accessible online. As a Stanford professor and co-founder of Coursera, Ng revolutionized how machine learning is taught, empowering millions globally with high-quality, scalable learning resources. The hosts explore his approachable teaching methods, the rise of MOOCs, and the long-term impact on industry and global talent pipelines. From foundational concepts like linear regression to specialized deep learning via deeplearning.ai, Andrew Ng’s education-first ethos helped democratize AI knowledge. The episode also touches on how his work enabled career pivots, upskilling, and industry-wide AI adoption—bringing education and innovation hand-in-hand. If you&apos;ve ever taken an online course in AI, chances are Andrew Ng helped shape your journey.]]></description>
    <content:encoded><![CDATA[In Episode 76 of &apos;100 Days of Data,&apos; Jonas and Amy spotlight Andrew Ng, the MOOC pioneer who transformed AI education by making it accessible online. As a Stanford professor and co-founder of Coursera, Ng revolutionized how machine learning is taught, empowering millions globally with high-quality, scalable learning resources. The hosts explore his approachable teaching methods, the rise of MOOCs, and the long-term impact on industry and global talent pipelines. From foundational concepts like linear regression to specialized deep learning via deeplearning.ai, Andrew Ng’s education-first ethos helped democratize AI knowledge. The episode also touches on how his work enabled career pivots, upskilling, and industry-wide AI adoption—bringing education and innovation hand-in-hand. If you&apos;ve ever taken an online course in AI, chances are Andrew Ng helped shape your journey.]]></content:encoded>
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    <pubDate>Fri, 06 Mar 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 75 - People: Geoffrey Hinton</itunes:title>
    <title>Episode 75 - People: Geoffrey Hinton</title>
    <itunes:summary><![CDATA[In Episode 75 of '100 Days of Data,' Jonas and Amy dive into the groundbreaking contributions of Geoffrey Hinton, often hailed as the 'godfather of deep learning.' They explore how Hinton's early pursuit of understanding human cognition led to revolutionary advances in neural networks and deep learning — technologies powering today’s AI solutions from fraud detection to voice recognition. The hosts break down key concepts like backpropagation and the rise of deep belief networks, revealing ho...]]></itunes:summary>
    <description><![CDATA[In Episode 75 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the groundbreaking contributions of Geoffrey Hinton, often hailed as the &apos;godfather of deep learning.&apos; They explore how Hinton&apos;s early pursuit of understanding human cognition led to revolutionary advances in neural networks and deep learning — technologies powering today’s AI solutions from fraud detection to voice recognition. The hosts break down key concepts like backpropagation and the rise of deep belief networks, revealing how Hinton’s persistence during AI’s toughest periods laid the groundwork for modern machine learning. With real-world applications and historical insight, this episode highlights how deep learning became a practical force in industries through Hinton’s vision and innovation.]]></description>
    <content:encoded><![CDATA[In Episode 75 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the groundbreaking contributions of Geoffrey Hinton, often hailed as the &apos;godfather of deep learning.&apos; They explore how Hinton&apos;s early pursuit of understanding human cognition led to revolutionary advances in neural networks and deep learning — technologies powering today’s AI solutions from fraud detection to voice recognition. The hosts break down key concepts like backpropagation and the rise of deep belief networks, revealing how Hinton’s persistence during AI’s toughest periods laid the groundwork for modern machine learning. With real-world applications and historical insight, this episode highlights how deep learning became a practical force in industries through Hinton’s vision and innovation.]]></content:encoded>
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    <pubDate>Thu, 05 Mar 2026 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 73 - People: Claude Shannon</itunes:title>
    <title>Episode 73 - People: Claude Shannon</title>
    <itunes:summary><![CDATA[In Episode 73 of '100 Days of Data,' hosts Jonas and Amy explore the groundbreaking legacy of Claude Shannon, the mathematician and electrical engineer who laid the foundation for the digital communication age. Known as the father of information theory, Shannon introduced mathematical principles that define how we measure, transmit, and compress data. The episode highlights pivotal concepts like entropy, channel capacity, and error correction, showing how these ideas revolutionized telecommun...]]></itunes:summary>
    <description><![CDATA[In Episode 73 of &apos;100 Days of Data,&apos; hosts Jonas and Amy explore the groundbreaking legacy of Claude Shannon, the mathematician and electrical engineer who laid the foundation for the digital communication age. Known as the father of information theory, Shannon introduced mathematical principles that define how we measure, transmit, and compress data. The episode highlights pivotal concepts like entropy, channel capacity, and error correction, showing how these ideas revolutionized telecommunications and laid the groundwork for AI, machine learning, and modern computing. By demystifying Shannon’s work, Jonas and Amy illustrate why understanding information theory is crucial for today’s business leaders, especially when making data-driven and AI-informed decisions.]]></description>
    <content:encoded><![CDATA[In Episode 73 of &apos;100 Days of Data,&apos; hosts Jonas and Amy explore the groundbreaking legacy of Claude Shannon, the mathematician and electrical engineer who laid the foundation for the digital communication age. Known as the father of information theory, Shannon introduced mathematical principles that define how we measure, transmit, and compress data. The episode highlights pivotal concepts like entropy, channel capacity, and error correction, showing how these ideas revolutionized telecommunications and laid the groundwork for AI, machine learning, and modern computing. By demystifying Shannon’s work, Jonas and Amy illustrate why understanding information theory is crucial for today’s business leaders, especially when making data-driven and AI-informed decisions.]]></content:encoded>
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    <pubDate>Tue, 03 Mar 2026 09:00:04 +0200</pubDate>
    <itunes:duration>468</itunes:duration>
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    <itunes:title>Episode 72 - People: Alan Turing</itunes:title>
    <title>Episode 72 - People: Alan Turing</title>
    <itunes:summary><![CDATA[In Episode 72 of '100 Days of Data,' Jonas and Amy dive into the life and legacy of Alan Turing, a foundational figure in modern computing and artificial intelligence. From his groundbreaking concept of the Turing Machine to his pivotal role in World War II codebreaking, Turing’s ideas shaped the evolution of computation and AI. The hosts explore how Turing's theories, including the famous Turing Test, laid the groundwork for today’s intelligent systems—from fraud detection to virtual assista...]]></itunes:summary>
    <description><![CDATA[In Episode 72 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the life and legacy of Alan Turing, a foundational figure in modern computing and artificial intelligence. From his groundbreaking concept of the Turing Machine to his pivotal role in World War II codebreaking, Turing’s ideas shaped the evolution of computation and AI. The hosts explore how Turing&apos;s theories, including the famous Turing Test, laid the groundwork for today’s intelligent systems—from fraud detection to virtual assistants. They also acknowledge his contributions to biology through mathematical modeling and reflect on the societal challenges he faced. This episode highlights why understanding Turing is crucial not only for technologists but for anyone aiming to leverage AI for meaningful, human-centered outcomes.]]></description>
    <content:encoded><![CDATA[In Episode 72 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the life and legacy of Alan Turing, a foundational figure in modern computing and artificial intelligence. From his groundbreaking concept of the Turing Machine to his pivotal role in World War II codebreaking, Turing’s ideas shaped the evolution of computation and AI. The hosts explore how Turing&apos;s theories, including the famous Turing Test, laid the groundwork for today’s intelligent systems—from fraud detection to virtual assistants. They also acknowledge his contributions to biology through mathematical modeling and reflect on the societal challenges he faced. This episode highlights why understanding Turing is crucial not only for technologists but for anyone aiming to leverage AI for meaningful, human-centered outcomes.]]></content:encoded>
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    <pubDate>Mon, 02 Mar 2026 09:00:04 +0200</pubDate>
    <itunes:duration>386</itunes:duration>
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    <itunes:title>Episode 71 - Checkpoint: Tools</itunes:title>
    <title>Episode 71 - Checkpoint: Tools</title>
    <itunes:summary><![CDATA[In Episode 71 of '100 Days of Data,' Jonas and Amy pause for a reflective checkpoint to evaluate the role of tools in your AI learning path. They explore how to choose tools that align with your skills, business needs, and data maturity — emphasizing function over flash. The episode unpacks what makes up a technology stack, why reflection is critical, and how to plan incremental tool adoption. With real-world examples from healthcare, finance, and retail, they illustrate the importance of sel...]]></itunes:summary>
    <description><![CDATA[In Episode 71 of &apos;100 Days of Data,&apos; Jonas and Amy pause for a reflective checkpoint to evaluate the role of tools in your AI learning path. They explore how to choose tools that align with your skills, business needs, and data maturity — emphasizing function over flash. The episode unpacks what makes up a technology stack, why reflection is critical, and how to plan incremental tool adoption. With real-world examples from healthcare, finance, and retail, they illustrate the importance of selecting the right tools for the right stage. Whether you&apos;re starting with basic spreadsheets or piloting ML models, the hosts guide you through building a thoughtful and adaptable toolkit that grows with your AI capabilities. It&apos;s a practical look at making smarter technology choices and staying intentional in your journey.]]></description>
    <content:encoded><![CDATA[In Episode 71 of &apos;100 Days of Data,&apos; Jonas and Amy pause for a reflective checkpoint to evaluate the role of tools in your AI learning path. They explore how to choose tools that align with your skills, business needs, and data maturity — emphasizing function over flash. The episode unpacks what makes up a technology stack, why reflection is critical, and how to plan incremental tool adoption. With real-world examples from healthcare, finance, and retail, they illustrate the importance of selecting the right tools for the right stage. Whether you&apos;re starting with basic spreadsheets or piloting ML models, the hosts guide you through building a thoughtful and adaptable toolkit that grows with your AI capabilities. It&apos;s a practical look at making smarter technology choices and staying intentional in your journey.]]></content:encoded>
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    <pubDate>Fri, 27 Feb 2026 09:00:04 +0200</pubDate>
    <itunes:duration>464</itunes:duration>
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    <itunes:title>Episode 70 - Data Tools: AutoML</itunes:title>
    <title>Episode 70 - Data Tools: AutoML</title>
    <itunes:summary><![CDATA[In Episode 70 of '100 Days of Data,' Jonas and Amy explore AutoML—Automated Machine Learning—and its transformative impact on the data science landscape. They break down how AutoML automates model building, from data preprocessing to model selection and hyperparameter tuning. Real-world use cases in healthcare, retail, finance, and manufacturing illustrate how AutoML drives efficiency, reduces the reliance on scarce expert talent, and accelerates business innovation. The episode also covers k...]]></itunes:summary>
    <description><![CDATA[In Episode 70 of &apos;100 Days of Data,&apos; Jonas and Amy explore AutoML—Automated Machine Learning—and its transformative impact on the data science landscape. They break down how AutoML automates model building, from data preprocessing to model selection and hyperparameter tuning. Real-world use cases in healthcare, retail, finance, and manufacturing illustrate how AutoML drives efficiency, reduces the reliance on scarce expert talent, and accelerates business innovation. The episode also covers key considerations like model interpretability, data quality, and governance, emphasizing that while AutoML empowers faster AI adoption, human insight remains critical for best results. Whether you&apos;re a data newcomer or a seasoned analyst, this episode unpacks AutoML as a powerful assistant in scaling AI efforts across industries.]]></description>
    <content:encoded><![CDATA[In Episode 70 of &apos;100 Days of Data,&apos; Jonas and Amy explore AutoML—Automated Machine Learning—and its transformative impact on the data science landscape. They break down how AutoML automates model building, from data preprocessing to model selection and hyperparameter tuning. Real-world use cases in healthcare, retail, finance, and manufacturing illustrate how AutoML drives efficiency, reduces the reliance on scarce expert talent, and accelerates business innovation. The episode also covers key considerations like model interpretability, data quality, and governance, emphasizing that while AutoML empowers faster AI adoption, human insight remains critical for best results. Whether you&apos;re a data newcomer or a seasoned analyst, this episode unpacks AutoML as a powerful assistant in scaling AI efforts across industries.]]></content:encoded>
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    <pubDate>Thu, 26 Feb 2026 09:00:05 +0200</pubDate>
    <itunes:duration>515</itunes:duration>
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    <itunes:title>Episode 69 - Data Tools: Scikit-learn</itunes:title>
    <title>Episode 69 - Data Tools: Scikit-learn</title>
    <itunes:summary><![CDATA[In Episode 69 of '100 Days of Data,' Jonas and Amy dive into Scikit-learn, the essential Python toolkit known as the 'Swiss army knife' for machine learning. They break down how this open-source library simplifies tasks like classification, regression, and clustering, empowering users to build models with ease and confidence. Through real-world examples—from customer segmentation in retail to predictive maintenance in manufacturing—the hosts illustrate how Scikit-learn streamlines data prepro...]]></itunes:summary>
    <description><![CDATA[In Episode 69 of &apos;100 Days of Data,&apos; Jonas and Amy dive into Scikit-learn, the essential Python toolkit known as the &apos;Swiss army knife&apos; for machine learning. They break down how this open-source library simplifies tasks like classification, regression, and clustering, empowering users to build models with ease and confidence. Through real-world examples—from customer segmentation in retail to predictive maintenance in manufacturing—the hosts illustrate how Scikit-learn streamlines data preprocessing, model building, and evaluation. They also highlight the benefits of its consistent API, robust documentation, and strong theoretical foundations, making it ideal for both beginners and pros. Whether you&apos;re developing a credit scoring model or forecasting product demand, Scikit-learn offers the tools you need to succeed across industries.]]></description>
    <content:encoded><![CDATA[In Episode 69 of &apos;100 Days of Data,&apos; Jonas and Amy dive into Scikit-learn, the essential Python toolkit known as the &apos;Swiss army knife&apos; for machine learning. They break down how this open-source library simplifies tasks like classification, regression, and clustering, empowering users to build models with ease and confidence. Through real-world examples—from customer segmentation in retail to predictive maintenance in manufacturing—the hosts illustrate how Scikit-learn streamlines data preprocessing, model building, and evaluation. They also highlight the benefits of its consistent API, robust documentation, and strong theoretical foundations, making it ideal for both beginners and pros. Whether you&apos;re developing a credit scoring model or forecasting product demand, Scikit-learn offers the tools you need to succeed across industries.]]></content:encoded>
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    <pubDate>Wed, 25 Feb 2026 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 68 - Data Tools: Hugging Face</itunes:title>
    <title>Episode 68 - Data Tools: Hugging Face</title>
    <itunes:summary><![CDATA[In Episode 68 of '100 Days of Data,' Jonas and Amy dive into Hugging Face, the go-to platform for accessing and deploying cutting-edge natural language processing tools. They explore how transformer models revolutionized NLP through attention mechanisms, enabling more accurate and context-aware language understanding. The hosts highlight Hugging Face’s impact on industries like finance and healthcare, showcasing how pre-trained models can be fine-tuned for specific use cases — from analyzing ...]]></itunes:summary>
    <description><![CDATA[In Episode 68 of &apos;100 Days of Data,&apos; Jonas and Amy dive into Hugging Face, the go-to platform for accessing and deploying cutting-edge natural language processing tools. They explore how transformer models revolutionized NLP through attention mechanisms, enabling more accurate and context-aware language understanding. The hosts highlight Hugging Face’s impact on industries like finance and healthcare, showcasing how pre-trained models can be fine-tuned for specific use cases — from analyzing clinical notes to detecting customer sentiment. With its open-source model hub, user-friendly APIs, and supportive community, Hugging Face lowers barriers to adoption and fosters innovation in AI. Tune in to understand how organizations can save time, cut costs, and enhance transparency by embracing this powerful AI ecosystem.]]></description>
    <content:encoded><![CDATA[In Episode 68 of &apos;100 Days of Data,&apos; Jonas and Amy dive into Hugging Face, the go-to platform for accessing and deploying cutting-edge natural language processing tools. They explore how transformer models revolutionized NLP through attention mechanisms, enabling more accurate and context-aware language understanding. The hosts highlight Hugging Face’s impact on industries like finance and healthcare, showcasing how pre-trained models can be fine-tuned for specific use cases — from analyzing clinical notes to detecting customer sentiment. With its open-source model hub, user-friendly APIs, and supportive community, Hugging Face lowers barriers to adoption and fosters innovation in AI. Tune in to understand how organizations can save time, cut costs, and enhance transparency by embracing this powerful AI ecosystem.]]></content:encoded>
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    <pubDate>Tue, 24 Feb 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 67 - Data Tools: PyTorch</itunes:title>
    <title>Episode 67 - Data Tools: PyTorch</title>
    <itunes:summary><![CDATA[In Episode 67 of '100 Days of Data,' Jonas and Amy explore PyTorch, the dynamic deep learning framework that has become a favorite among AI researchers and developers. They explain how PyTorch's flexible, Pythonic design simplifies model building and experimentation, making it ideal for both rapid prototyping and real-world deployment. From its use of dynamic computation graphs to its robust ecosystem—including tools like torchvision and torchaudio—PyTorch is highlighted as a bridge between e...]]></itunes:summary>
    <description><![CDATA[In Episode 67 of &apos;100 Days of Data,&apos; Jonas and Amy explore PyTorch, the dynamic deep learning framework that has become a favorite among AI researchers and developers. They explain how PyTorch&apos;s flexible, Pythonic design simplifies model building and experimentation, making it ideal for both rapid prototyping and real-world deployment. From its use of dynamic computation graphs to its robust ecosystem—including tools like torchvision and torchaudio—PyTorch is highlighted as a bridge between experimental research and production-ready AI solutions. The hosts walk through real-world examples in finance, healthcare, and automotive industries, underscoring PyTorch&apos;s transformative impact. Whether you’re managing AI workflows or coding models yourself, this episode illustrates why PyTorch has earned its place at the heart of modern deep learning.]]></description>
    <content:encoded><![CDATA[In Episode 67 of &apos;100 Days of Data,&apos; Jonas and Amy explore PyTorch, the dynamic deep learning framework that has become a favorite among AI researchers and developers. They explain how PyTorch&apos;s flexible, Pythonic design simplifies model building and experimentation, making it ideal for both rapid prototyping and real-world deployment. From its use of dynamic computation graphs to its robust ecosystem—including tools like torchvision and torchaudio—PyTorch is highlighted as a bridge between experimental research and production-ready AI solutions. The hosts walk through real-world examples in finance, healthcare, and automotive industries, underscoring PyTorch&apos;s transformative impact. Whether you’re managing AI workflows or coding models yourself, this episode illustrates why PyTorch has earned its place at the heart of modern deep learning.]]></content:encoded>
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    <pubDate>Mon, 23 Feb 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 66 - Data Tools: TensorFlow</itunes:title>
    <title>Episode 66 - Data Tools: TensorFlow</title>
    <itunes:summary><![CDATA[In Episode 66 of '100 Days of Data,' Jonas and Amy delve into TensorFlow—Google’s open-source machine learning framework that has become a staple across industries. They explain how TensorFlow uses data flow graphs and tensors to power deep learning, enabling everything from voice assistants to medical diagnostics. The duo breaks down TensorFlow’s evolution from static graphs to eager execution, highlighting how this shift improved flexibility and usability. They also explore TensorFlow’s ver...]]></itunes:summary>
    <description><![CDATA[In Episode 66 of &apos;100 Days of Data,&apos; Jonas and Amy delve into TensorFlow—Google’s open-source machine learning framework that has become a staple across industries. They explain how TensorFlow uses data flow graphs and tensors to power deep learning, enabling everything from voice assistants to medical diagnostics. The duo breaks down TensorFlow’s evolution from static graphs to eager execution, highlighting how this shift improved flexibility and usability. They also explore TensorFlow’s versatile ecosystem, including TensorFlow Lite, TensorFlow Extended, and TensorFlow.js, making it a comprehensive solution for research, production, and deployment. With real-world examples from healthcare and retail, this episode illustrates how TensorFlow empowers businesses to build scalable, AI-driven systems. Whether you&apos;re a seasoned developer or just exploring AI tools, this episode offers valuable insights into one of the most influential ML frameworks today.]]></description>
    <content:encoded><![CDATA[In Episode 66 of &apos;100 Days of Data,&apos; Jonas and Amy delve into TensorFlow—Google’s open-source machine learning framework that has become a staple across industries. They explain how TensorFlow uses data flow graphs and tensors to power deep learning, enabling everything from voice assistants to medical diagnostics. The duo breaks down TensorFlow’s evolution from static graphs to eager execution, highlighting how this shift improved flexibility and usability. They also explore TensorFlow’s versatile ecosystem, including TensorFlow Lite, TensorFlow Extended, and TensorFlow.js, making it a comprehensive solution for research, production, and deployment. With real-world examples from healthcare and retail, this episode illustrates how TensorFlow empowers businesses to build scalable, AI-driven systems. Whether you&apos;re a seasoned developer or just exploring AI tools, this episode offers valuable insights into one of the most influential ML frameworks today.]]></content:encoded>
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    <pubDate>Fri, 20 Feb 2026 09:00:04 +0200</pubDate>
    <itunes:duration>440</itunes:duration>
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  <item>
    <itunes:title>Episode 65 - Data Tools: Power BI &amp; Tableau</itunes:title>
    <title>Episode 65 - Data Tools: Power BI &amp; Tableau</title>
    <itunes:summary><![CDATA[In Episode 65 of '100 Days of Data,' Jonas and Amy explore the evolution of business intelligence tools, focusing on Power BI and Tableau. They discuss how visualization platforms have progressed from static spreadsheets to dynamic dashboards that drive understanding and action. Listeners gain insight into how these tools transform raw data into intuitive visuals, reduce cognitive load, and support faster decision-making across industries like retail, healthcare, and finance. The hosts compar...]]></itunes:summary>
    <description><![CDATA[In Episode 65 of &apos;100 Days of Data,&apos; Jonas and Amy explore the evolution of business intelligence tools, focusing on Power BI and Tableau. They discuss how visualization platforms have progressed from static spreadsheets to dynamic dashboards that drive understanding and action. Listeners gain insight into how these tools transform raw data into intuitive visuals, reduce cognitive load, and support faster decision-making across industries like retail, healthcare, and finance. The hosts compare features, integration options, pricing models, and use cases, helping professionals choose the right tool based on workflow, ecosystem, and analytical needs. They also highlight how built-in AI features like Explain Data and automated forecasts bring advanced analytics to non-technical users. Whether you&apos;re exploring real-time reporting or in-depth analysis, this episode helps demystify the strengths and trade-offs of two leading BI platforms.]]></description>
    <content:encoded><![CDATA[In Episode 65 of &apos;100 Days of Data,&apos; Jonas and Amy explore the evolution of business intelligence tools, focusing on Power BI and Tableau. They discuss how visualization platforms have progressed from static spreadsheets to dynamic dashboards that drive understanding and action. Listeners gain insight into how these tools transform raw data into intuitive visuals, reduce cognitive load, and support faster decision-making across industries like retail, healthcare, and finance. The hosts compare features, integration options, pricing models, and use cases, helping professionals choose the right tool based on workflow, ecosystem, and analytical needs. They also highlight how built-in AI features like Explain Data and automated forecasts bring advanced analytics to non-technical users. Whether you&apos;re exploring real-time reporting or in-depth analysis, this episode helps demystify the strengths and trade-offs of two leading BI platforms.]]></content:encoded>
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    <pubDate>Thu, 19 Feb 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 64 - Data Tools: SQL</itunes:title>
    <title>Episode 64 - Data Tools: SQL</title>
    <itunes:summary><![CDATA[In Episode 64 of '100 Days of Data,' Jonas and Amy dive into SQL—the foundational language used to communicate with relational databases. They explain how SQL enables users to ask questions, extract insights, and manage data through tables, queries, and joins. From simple commands like SELECT and WHERE to complex operations like joins and indexing, the episode demystifies SQL’s syntax and structure. Real-world examples from healthcare, retail, and finance illustrate SQL’s everyday impact on d...]]></itunes:summary>
    <description><![CDATA[In Episode 64 of &apos;100 Days of Data,&apos; Jonas and Amy dive into SQL—the foundational language used to communicate with relational databases. They explain how SQL enables users to ask questions, extract insights, and manage data through tables, queries, and joins. From simple commands like SELECT and WHERE to complex operations like joins and indexing, the episode demystifies SQL’s syntax and structure. Real-world examples from healthcare, retail, and finance illustrate SQL’s everyday impact on decision-making and automation. Whether you&apos;re manipulating real-time inventory or analyzing patient outcomes, SQL is a critical skill for any data-aware professional. The hosts also highlight SQL’s evolving role in cloud services and its growing flexibility with semi-structured data. This episode is both a practical guide and a strategic overview of why SQL remains central to working with data in AI-driven environments.]]></description>
    <content:encoded><![CDATA[In Episode 64 of &apos;100 Days of Data,&apos; Jonas and Amy dive into SQL—the foundational language used to communicate with relational databases. They explain how SQL enables users to ask questions, extract insights, and manage data through tables, queries, and joins. From simple commands like SELECT and WHERE to complex operations like joins and indexing, the episode demystifies SQL’s syntax and structure. Real-world examples from healthcare, retail, and finance illustrate SQL’s everyday impact on decision-making and automation. Whether you&apos;re manipulating real-time inventory or analyzing patient outcomes, SQL is a critical skill for any data-aware professional. The hosts also highlight SQL’s evolving role in cloud services and its growing flexibility with semi-structured data. This episode is both a practical guide and a strategic overview of why SQL remains central to working with data in AI-driven environments.]]></content:encoded>
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    <pubDate>Wed, 18 Feb 2026 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 63 - Data Tools: R</itunes:title>
    <title>Episode 63 - Data Tools: R</title>
    <itunes:summary><![CDATA[In Episode 63 of “100 Days of Data,” Jonas and Amy dive into R, the beloved statistical programming language designed for data analysis. They explore how R’s origin as a tool for statisticians has made it essential in industries from healthcare to retail, delivering powerful statistical methods, rich visualizations, and reproducible reporting. With real-world case studies — from hospital networks improving patient care to retailers optimizing inventory — they show how R translates data into a...]]></itunes:summary>
    <description><![CDATA[In Episode 63 of “100 Days of Data,” Jonas and Amy dive into R, the beloved statistical programming language designed for data analysis. They explore how R’s origin as a tool for statisticians has made it essential in industries from healthcare to retail, delivering powerful statistical methods, rich visualizations, and reproducible reporting. With real-world case studies — from hospital networks improving patient care to retailers optimizing inventory — they show how R translates data into actionable insights. The hosts also compare R to Python, offering guidance on when each tool shines. Practical advice for organizations adopting R, the benefits of R Markdown, and the strength of the R community round out this informative episode tailored for those looking to deepen their analytical toolkit.]]></description>
    <content:encoded><![CDATA[In Episode 63 of “100 Days of Data,” Jonas and Amy dive into R, the beloved statistical programming language designed for data analysis. They explore how R’s origin as a tool for statisticians has made it essential in industries from healthcare to retail, delivering powerful statistical methods, rich visualizations, and reproducible reporting. With real-world case studies — from hospital networks improving patient care to retailers optimizing inventory — they show how R translates data into actionable insights. The hosts also compare R to Python, offering guidance on when each tool shines. Practical advice for organizations adopting R, the benefits of R Markdown, and the strength of the R community round out this informative episode tailored for those looking to deepen their analytical toolkit.]]></content:encoded>
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    <pubDate>Tue, 17 Feb 2026 09:00:04 +0200</pubDate>
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  <item>
    <itunes:title>Episode 62 - Data Tools: Python</itunes:title>
    <title>Episode 62 - Data Tools: Python</title>
    <itunes:summary><![CDATA[In Episode 62 of '100 Days of Data,' Jonas and Amy explore why Python is often called the language of data science. They discuss its accessible syntax, wide-ranging libraries like Pandas and NumPy, and the power of its open-source community. From retail to automotive, Python is helping teams analyze trends, automate processes, and extract insights faster—often without waiting on IT. The episode also emphasizes the importance of pairing Python adoption with best practices to avoid messy code. ...]]></itunes:summary>
    <description><![CDATA[In Episode 62 of &apos;100 Days of Data,&apos; Jonas and Amy explore why Python is often called the language of data science. They discuss its accessible syntax, wide-ranging libraries like Pandas and NumPy, and the power of its open-source community. From retail to automotive, Python is helping teams analyze trends, automate processes, and extract insights faster—often without waiting on IT. The episode also emphasizes the importance of pairing Python adoption with best practices to avoid messy code. Whether you&apos;re a business analyst or an AI researcher, Python bridges teams and transforms data into action. This episode sets the foundation for understanding how Python powers everything from automation to predictive analytics across industries.]]></description>
    <content:encoded><![CDATA[In Episode 62 of &apos;100 Days of Data,&apos; Jonas and Amy explore why Python is often called the language of data science. They discuss its accessible syntax, wide-ranging libraries like Pandas and NumPy, and the power of its open-source community. From retail to automotive, Python is helping teams analyze trends, automate processes, and extract insights faster—often without waiting on IT. The episode also emphasizes the importance of pairing Python adoption with best practices to avoid messy code. Whether you&apos;re a business analyst or an AI researcher, Python bridges teams and transforms data into action. This episode sets the foundation for understanding how Python powers everything from automation to predictive analytics across industries.]]></content:encoded>
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    <pubDate>Mon, 16 Feb 2026 09:00:04 +0200</pubDate>
    <itunes:duration>378</itunes:duration>
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  <item>
    <itunes:title>Episode 61 - Checkpoint: Industry Applications</itunes:title>
    <title>Episode 61 - Checkpoint: Industry Applications</title>
    <itunes:summary><![CDATA[In Episode 61 of '100 Days of Data,' Jonas and Amy hit the pause button to reflect on how AI and data are transforming real-world industries. From healthcare to finance, automotive to retail, the hosts revisit some of the most compelling use cases discussed in previous episodes. This checkpoint offers valuable insights into how data science concepts are applied in practical settings — improving patient outcomes, reducing fraud, enabling smart vehicles, and optimizing retail supply chains. The...]]></itunes:summary>
    <description><![CDATA[In Episode 61 of &apos;100 Days of Data,&apos; Jonas and Amy hit the pause button to reflect on how AI and data are transforming real-world industries. From healthcare to finance, automotive to retail, the hosts revisit some of the most compelling use cases discussed in previous episodes. This checkpoint offers valuable insights into how data science concepts are applied in practical settings — improving patient outcomes, reducing fraud, enabling smart vehicles, and optimizing retail supply chains. They explore the importance of aligning business goals with AI tools, the need for ethical considerations, and how every industry — no matter how traditional — can find value in AI-driven solutions. Whether you&apos;re in tech, healthcare, or consumer products, this episode provides a vivid snapshot of AI’s expanding footprint and reminds listeners that impactful AI starts with high-quality data and clear intent.]]></description>
    <content:encoded><![CDATA[In Episode 61 of &apos;100 Days of Data,&apos; Jonas and Amy hit the pause button to reflect on how AI and data are transforming real-world industries. From healthcare to finance, automotive to retail, the hosts revisit some of the most compelling use cases discussed in previous episodes. This checkpoint offers valuable insights into how data science concepts are applied in practical settings — improving patient outcomes, reducing fraud, enabling smart vehicles, and optimizing retail supply chains. They explore the importance of aligning business goals with AI tools, the need for ethical considerations, and how every industry — no matter how traditional — can find value in AI-driven solutions. Whether you&apos;re in tech, healthcare, or consumer products, this episode provides a vivid snapshot of AI’s expanding footprint and reminds listeners that impactful AI starts with high-quality data and clear intent.]]></content:encoded>
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    <pubDate>Fri, 13 Feb 2026 09:00:04 +0200</pubDate>
    <itunes:duration>569</itunes:duration>
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    <itunes:title>Episode 60 - AI in Social Media</itunes:title>
    <title>Episode 60 - AI in Social Media</title>
    <itunes:summary><![CDATA[In Episode 60 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence drives social media feeds and the reasons behind their addictive nature. They unpack the role of algorithms in selecting personalized content, how engagement metrics shape your experience, and the unintended consequences like echo chambers and feedback loops. The duo explains recommendation systems, content moderation powered by NLP, and why these AI models are both powerful tools and ethical minefields. Dr...]]></itunes:summary>
    <description><![CDATA[In Episode 60 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence drives social media feeds and the reasons behind their addictive nature. They unpack the role of algorithms in selecting personalized content, how engagement metrics shape your experience, and the unintended consequences like echo chambers and feedback loops. The duo explains recommendation systems, content moderation powered by NLP, and why these AI models are both powerful tools and ethical minefields. Drawing from real-world stories in advertising and healthcare, Amy and Jonas offer insights into how businesses can better navigate platform algorithms. They discuss the balancing act between engagement optimization and responsible content delivery, giving listeners a behind-the-curtain look at the AI mechanics shaping digital interaction. Whether you’re a tech enthusiast or a marketing leader, this episode offers valuable takeaways on the hidden forces steering your scroll.]]></description>
    <content:encoded><![CDATA[In Episode 60 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence drives social media feeds and the reasons behind their addictive nature. They unpack the role of algorithms in selecting personalized content, how engagement metrics shape your experience, and the unintended consequences like echo chambers and feedback loops. The duo explains recommendation systems, content moderation powered by NLP, and why these AI models are both powerful tools and ethical minefields. Drawing from real-world stories in advertising and healthcare, Amy and Jonas offer insights into how businesses can better navigate platform algorithms. They discuss the balancing act between engagement optimization and responsible content delivery, giving listeners a behind-the-curtain look at the AI mechanics shaping digital interaction. Whether you’re a tech enthusiast or a marketing leader, this episode offers valuable takeaways on the hidden forces steering your scroll.]]></content:encoded>
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    <pubDate>Mon, 09 Feb 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 59 - AI in Sports</itunes:title>
    <title>Episode 59 - AI in Sports</title>
    <itunes:summary><![CDATA[In Episode 59 of '100 Days of Data,' Jonas and Amy explore how AI is transforming the sports industry, from enhancing player performance and preventing injuries to fine-tuning game strategy and enriching fan engagement. They dive into real-life examples, such as AI-powered training regimens, predictive modeling for season simulations, and real-time analytics like NFL’s Next Gen Stats. The conversation also covers the data collection technologies behind these innovations—from GPS trackers to c...]]></itunes:summary>
    <description><![CDATA[In Episode 59 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI is transforming the sports industry, from enhancing player performance and preventing injuries to fine-tuning game strategy and enriching fan engagement. They dive into real-life examples, such as AI-powered training regimens, predictive modeling for season simulations, and real-time analytics like NFL’s Next Gen Stats. The conversation also covers the data collection technologies behind these innovations—from GPS trackers to computer vision—and the ethical considerations around biometric data. This episode illustrates how AI is not just reshaping gameplay but also revolutionizing the business and experience of sports through data-driven decision-making.]]></description>
    <content:encoded><![CDATA[In Episode 59 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI is transforming the sports industry, from enhancing player performance and preventing injuries to fine-tuning game strategy and enriching fan engagement. They dive into real-life examples, such as AI-powered training regimens, predictive modeling for season simulations, and real-time analytics like NFL’s Next Gen Stats. The conversation also covers the data collection technologies behind these innovations—from GPS trackers to computer vision—and the ethical considerations around biometric data. This episode illustrates how AI is not just reshaping gameplay but also revolutionizing the business and experience of sports through data-driven decision-making.]]></content:encoded>
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    <pubDate>Fri, 06 Feb 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 58 - AI in Manufacturing</itunes:title>
    <title>Episode 58 - AI in Manufacturing</title>
    <itunes:summary><![CDATA[In Episode 58 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is transforming the manufacturing industry as part of the Industry 4.0 revolution. They dive into the roles of smart robots, predictive maintenance, and the Internet of Things (IoT) in creating more efficient, responsive, and cost-effective production lines. Real-world examples—from predictive analytics in automotive assembly to digital twins in food packaging—demonstrate how data-driven insights are reshap...]]></itunes:summary>
    <description><![CDATA[In Episode 58 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is transforming the manufacturing industry as part of the Industry 4.0 revolution. They dive into the roles of smart robots, predictive maintenance, and the Internet of Things (IoT) in creating more efficient, responsive, and cost-effective production lines. Real-world examples—from predictive analytics in automotive assembly to digital twins in food packaging—demonstrate how data-driven insights are reshaping operations and quality control. The episode also addresses key challenges like data integration, cybersecurity, and change management, offering a comprehensive look at both the promise and the pitfalls of AI in manufacturing. Whether you’re an engineer, executive, or AI enthusiast, this episode breaks down complex systems into clear, practical insights for the modern factory.]]></description>
    <content:encoded><![CDATA[In Episode 58 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is transforming the manufacturing industry as part of the Industry 4.0 revolution. They dive into the roles of smart robots, predictive maintenance, and the Internet of Things (IoT) in creating more efficient, responsive, and cost-effective production lines. Real-world examples—from predictive analytics in automotive assembly to digital twins in food packaging—demonstrate how data-driven insights are reshaping operations and quality control. The episode also addresses key challenges like data integration, cybersecurity, and change management, offering a comprehensive look at both the promise and the pitfalls of AI in manufacturing. Whether you’re an engineer, executive, or AI enthusiast, this episode breaks down complex systems into clear, practical insights for the modern factory.]]></content:encoded>
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    <pubDate>Thu, 05 Feb 2026 09:00:05 +0200</pubDate>
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    <itunes:title>Episode 57 - AI in Entertainment</itunes:title>
    <title>Episode 57 - AI in Entertainment</title>
    <itunes:summary><![CDATA[In Episode 57 of '100 Days of Data,' Jonas and Amy explore how AI powers personalized experiences on platforms like Netflix and Spotify. They break down the core technologies behind recommendation systems—collaborative and content-based filtering—and how these systems evolve with hybrid models and deep learning. The hosts also tackle key challenges such as the cold start problem, filter bubbles, and privacy concerns, offering insights into how algorithms adapt to real-time user behavior. Real...]]></itunes:summary>
    <description><![CDATA[In Episode 57 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI powers personalized experiences on platforms like Netflix and Spotify. They break down the core technologies behind recommendation systems—collaborative and content-based filtering—and how these systems evolve with hybrid models and deep learning. The hosts also tackle key challenges such as the cold start problem, filter bubbles, and privacy concerns, offering insights into how algorithms adapt to real-time user behavior. Real-world examples, from music streaming in cars to in-game personalization, illustrate how AI keeps users engaged and businesses thriving. This episode is a deep dive into the sophisticated data-driven systems that turn endless entertainment options into tailored, engaging experiences.]]></description>
    <content:encoded><![CDATA[In Episode 57 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI powers personalized experiences on platforms like Netflix and Spotify. They break down the core technologies behind recommendation systems—collaborative and content-based filtering—and how these systems evolve with hybrid models and deep learning. The hosts also tackle key challenges such as the cold start problem, filter bubbles, and privacy concerns, offering insights into how algorithms adapt to real-time user behavior. Real-world examples, from music streaming in cars to in-game personalization, illustrate how AI keeps users engaged and businesses thriving. This episode is a deep dive into the sophisticated data-driven systems that turn endless entertainment options into tailored, engaging experiences.]]></content:encoded>
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    <pubDate>Wed, 04 Feb 2026 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 56 - AI in Logistics</itunes:title>
    <title>Episode 56 - AI in Logistics</title>
    <itunes:summary><![CDATA[In Episode 56 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is revolutionizing the logistics industry—from warehouse automation to predictive analytics. They break down key AI concepts like optimization and machine learning, illustrating how they’re used to streamline supply chains, forecast demand, and manage risk. Real-world examples, including autonomous delivery fleets and AI-driven demand planning during the pandemic, highlight the tangible business and social ...]]></itunes:summary>
    <description><![CDATA[In Episode 56 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is revolutionizing the logistics industry—from warehouse automation to predictive analytics. They break down key AI concepts like optimization and machine learning, illustrating how they’re used to streamline supply chains, forecast demand, and manage risk. Real-world examples, including autonomous delivery fleets and AI-driven demand planning during the pandemic, highlight the tangible business and social impact of these technologies. The hosts also discuss implementation challenges such as data quality, system integration, and explainability, offering practical advice for organizations embarking on their AI journeys. Whether you&apos;re in retail, manufacturing, or healthcare, this episode delivers insights into how AI can make supply chains faster, smarter, and more resilient.]]></description>
    <content:encoded><![CDATA[In Episode 56 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is revolutionizing the logistics industry—from warehouse automation to predictive analytics. They break down key AI concepts like optimization and machine learning, illustrating how they’re used to streamline supply chains, forecast demand, and manage risk. Real-world examples, including autonomous delivery fleets and AI-driven demand planning during the pandemic, highlight the tangible business and social impact of these technologies. The hosts also discuss implementation challenges such as data quality, system integration, and explainability, offering practical advice for organizations embarking on their AI journeys. Whether you&apos;re in retail, manufacturing, or healthcare, this episode delivers insights into how AI can make supply chains faster, smarter, and more resilient.]]></content:encoded>
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    <pubDate>Tue, 03 Feb 2026 09:00:05 +0200</pubDate>
    <itunes:duration>463</itunes:duration>
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  <item>
    <itunes:title>Episode 55 - AI in Education</itunes:title>
    <title>Episode 55 - AI in Education</title>
    <itunes:summary><![CDATA[In Episode 55 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is transforming education through personalized learning and advanced edtech solutions. They dive into the mechanics of AI-powered tutoring, from Bayesian Knowledge Tracing to adaptive lesson delivery, and highlight real-world applications from platforms like DreamBox, Coursera, and Duolingo. The episode also touches on key challenges, such as data quality, algorithmic bias, and the ethical considerations su...]]></itunes:summary>
    <description><![CDATA[In Episode 55 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is transforming education through personalized learning and advanced edtech solutions. They dive into the mechanics of AI-powered tutoring, from Bayesian Knowledge Tracing to adaptive lesson delivery, and highlight real-world applications from platforms like DreamBox, Coursera, and Duolingo. The episode also touches on key challenges, such as data quality, algorithmic bias, and the ethical considerations surrounding student privacy. Listeners will gain insights into how AI supports both learners and educators, enhancing engagement, efficiency, and outcomes across K-12, corporate training, and lifelong learning paths. From gamified simulations to AI teaching assistants, this discussion makes clear that education is no longer one-size-fits-all—thanks to data-driven innovation.]]></description>
    <content:encoded><![CDATA[In Episode 55 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is transforming education through personalized learning and advanced edtech solutions. They dive into the mechanics of AI-powered tutoring, from Bayesian Knowledge Tracing to adaptive lesson delivery, and highlight real-world applications from platforms like DreamBox, Coursera, and Duolingo. The episode also touches on key challenges, such as data quality, algorithmic bias, and the ethical considerations surrounding student privacy. Listeners will gain insights into how AI supports both learners and educators, enhancing engagement, efficiency, and outcomes across K-12, corporate training, and lifelong learning paths. From gamified simulations to AI teaching assistants, this discussion makes clear that education is no longer one-size-fits-all—thanks to data-driven innovation.]]></content:encoded>
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    <pubDate>Mon, 02 Feb 2026 09:00:03 +0200</pubDate>
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  <item>
    <itunes:title>Episode 54 - AI in Government</itunes:title>
    <title>Episode 54 - AI in Government</title>
    <itunes:summary><![CDATA[In Episode 54 of '100 Days of Data,' Jonas and Amy explore how AI is revolutionizing government operations, from streamlining digital services to enabling predictive policymaking. They discuss how digitalization lays the groundwork for innovation, allowing governments to automate workflows, analyze large datasets, and proactively address public needs. Through real-world examples—from AI chatbots in the UK tax system to predictive fire risk models in New York—they illustrate how AI can enhance...]]></itunes:summary>
    <description><![CDATA[In Episode 54 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI is revolutionizing government operations, from streamlining digital services to enabling predictive policymaking. They discuss how digitalization lays the groundwork for innovation, allowing governments to automate workflows, analyze large datasets, and proactively address public needs. Through real-world examples—from AI chatbots in the UK tax system to predictive fire risk models in New York—they illustrate how AI can enhance efficiency, accessibility, and decision-making. They also address the challenges, including data privacy, bias, and the need for explainable models, emphasizing the importance of ethical frameworks and human oversight. Whether it&apos;s improving service delivery or public trust, this episode highlights why responsible AI is critical to the future of government.]]></description>
    <content:encoded><![CDATA[In Episode 54 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI is revolutionizing government operations, from streamlining digital services to enabling predictive policymaking. They discuss how digitalization lays the groundwork for innovation, allowing governments to automate workflows, analyze large datasets, and proactively address public needs. Through real-world examples—from AI chatbots in the UK tax system to predictive fire risk models in New York—they illustrate how AI can enhance efficiency, accessibility, and decision-making. They also address the challenges, including data privacy, bias, and the need for explainable models, emphasizing the importance of ethical frameworks and human oversight. Whether it&apos;s improving service delivery or public trust, this episode highlights why responsible AI is critical to the future of government.]]></content:encoded>
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    <pubDate>Fri, 30 Jan 2026 09:00:03 +0200</pubDate>
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  <item>
    <itunes:title>Episode 53 - AI in Agriculture</itunes:title>
    <title>Episode 53 - AI in Agriculture</title>
    <itunes:summary><![CDATA[In Episode 53 of '100 Days of Data,' hosts Jonas and Amy explore how AI is revolutionizing agriculture through precision farming and crop prediction. They discuss how data from soil sensors, drones, and satellite imagery is used to optimize irrigation, fertilization, and harvest timing. Real-world examples from farms in the Midwest, California, and India highlight the powerful role of AI in increasing yields, conserving resources, and mitigating risks like pest outbreaks. The conversation als...]]></itunes:summary>
    <description><![CDATA[In Episode 53 of &apos;100 Days of Data,&apos; hosts Jonas and Amy explore how AI is revolutionizing agriculture through precision farming and crop prediction. They discuss how data from soil sensors, drones, and satellite imagery is used to optimize irrigation, fertilization, and harvest timing. Real-world examples from farms in the Midwest, California, and India highlight the powerful role of AI in increasing yields, conserving resources, and mitigating risks like pest outbreaks. The conversation also addresses the challenges of adoption, including high upfront costs and the need for clean, reliable data. With insights into IoT integration, adaptive AI models, and the cultural shift required for tech adoption, this episode provides a comprehensive look at how farming is becoming more data-driven, efficient, and sustainable.]]></description>
    <content:encoded><![CDATA[In Episode 53 of &apos;100 Days of Data,&apos; hosts Jonas and Amy explore how AI is revolutionizing agriculture through precision farming and crop prediction. They discuss how data from soil sensors, drones, and satellite imagery is used to optimize irrigation, fertilization, and harvest timing. Real-world examples from farms in the Midwest, California, and India highlight the powerful role of AI in increasing yields, conserving resources, and mitigating risks like pest outbreaks. The conversation also addresses the challenges of adoption, including high upfront costs and the need for clean, reliable data. With insights into IoT integration, adaptive AI models, and the cultural shift required for tech adoption, this episode provides a comprehensive look at how farming is becoming more data-driven, efficient, and sustainable.]]></content:encoded>
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    <pubDate>Thu, 29 Jan 2026 09:00:05 +0200</pubDate>
    <itunes:duration>418</itunes:duration>
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  <item>
    <itunes:title>Episode 52 - AI in Energy</itunes:title>
    <title>Episode 52 - AI in Energy</title>
    <itunes:summary><![CDATA[In Episode 52 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is revolutionizing the energy industry — from managing smart grids to enabling predictive maintenance and renewable integration. They explain how AI processes real-time sensor data to predict demand, prevent equipment failures, and even orchestrate energy flows between consumers and producers. Through practical examples like EV charging, wind farm optimization, and anomaly detection, the duo highlights AI's...]]></itunes:summary>
    <description><![CDATA[In Episode 52 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is revolutionizing the energy industry — from managing smart grids to enabling predictive maintenance and renewable integration. They explain how AI processes real-time sensor data to predict demand, prevent equipment failures, and even orchestrate energy flows between consumers and producers. Through practical examples like EV charging, wind farm optimization, and anomaly detection, the duo highlights AI&apos;s role in making energy systems more adaptive, efficient, and sustainable. Listeners will also gain insight into some critical challenges, including outdated infrastructure and complex regulations. Whether you&apos;re new to energy tech or deeply embedded in the sector, this episode offers a clear, engaging look at how AI is powering the future of energy.]]></description>
    <content:encoded><![CDATA[In Episode 52 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is revolutionizing the energy industry — from managing smart grids to enabling predictive maintenance and renewable integration. They explain how AI processes real-time sensor data to predict demand, prevent equipment failures, and even orchestrate energy flows between consumers and producers. Through practical examples like EV charging, wind farm optimization, and anomaly detection, the duo highlights AI&apos;s role in making energy systems more adaptive, efficient, and sustainable. Listeners will also gain insight into some critical challenges, including outdated infrastructure and complex regulations. Whether you&apos;re new to energy tech or deeply embedded in the sector, this episode offers a clear, engaging look at how AI is powering the future of energy.]]></content:encoded>
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    <pubDate>Wed, 28 Jan 2026 09:00:03 +0200</pubDate>
    <itunes:duration>377</itunes:duration>
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  <item>
    <itunes:title>Episode 50 - What’s Next?</itunes:title>
    <title>Episode 50 - What’s Next?</title>
    <itunes:summary><![CDATA[In Episode 50 of '100 Days of Data,' Jonas and Amy fast-forward to the year 2050, exploring how data and AI could redefine the way we live, work, and relate to technology. Through the lens of foresight—a structured approach to speculating about the future—they discuss how current trends in AI, from autonomous vehicles to personalized healthcare, are shaping multiple potential futures. The duo reflects on both opportunities and ethical challenges that come with living in a data-driven world, s...]]></itunes:summary>
    <description><![CDATA[In Episode 50 of &apos;100 Days of Data,&apos; Jonas and Amy fast-forward to the year 2050, exploring how data and AI could redefine the way we live, work, and relate to technology. Through the lens of foresight—a structured approach to speculating about the future—they discuss how current trends in AI, from autonomous vehicles to personalized healthcare, are shaping multiple potential futures. The duo reflects on both opportunities and ethical challenges that come with living in a data-driven world, such as digital inequality, privacy concerns, and human–machine symbiosis. They emphasize that foresight isn&apos;t just for futurists—it’s a crucial tool for businesses and professionals looking to navigate uncertainty with better strategy and resilience. Whether it’s smart cities or AI-augmented workplaces, this episode explores what’s next and how to prepare for it.]]></description>
    <content:encoded><![CDATA[In Episode 50 of &apos;100 Days of Data,&apos; Jonas and Amy fast-forward to the year 2050, exploring how data and AI could redefine the way we live, work, and relate to technology. Through the lens of foresight—a structured approach to speculating about the future—they discuss how current trends in AI, from autonomous vehicles to personalized healthcare, are shaping multiple potential futures. The duo reflects on both opportunities and ethical challenges that come with living in a data-driven world, such as digital inequality, privacy concerns, and human–machine symbiosis. They emphasize that foresight isn&apos;t just for futurists—it’s a crucial tool for businesses and professionals looking to navigate uncertainty with better strategy and resilience. Whether it’s smart cities or AI-augmented workplaces, this episode explores what’s next and how to prepare for it.]]></content:encoded>
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    <pubDate>Mon, 26 Jan 2026 18:17:32 +0200</pubDate>
    <itunes:duration>448</itunes:duration>
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  <item>
    <itunes:title>Episode 49 - The Singularity Debate</itunes:title>
    <title>Episode 49 - The Singularity Debate</title>
    <itunes:summary><![CDATA[In Episode 49 of '100 Days of Data,' Jonas and Amy tackle the provocative question: will AI surpass human intelligence? They explore the concept of the technological singularity, breaking down key terms like Artificial General Intelligence (AGI) and superintelligence. The discussion ranges from current AI capabilities to speculative futures, examining both the excitement and concerns surrounding these advancements. With practical insights from business and academia, they highlight the ethical...]]></itunes:summary>
    <description><![CDATA[In Episode 49 of &apos;100 Days of Data,&apos; Jonas and Amy tackle the provocative question: will AI surpass human intelligence? They explore the concept of the technological singularity, breaking down key terms like Artificial General Intelligence (AGI) and superintelligence. The discussion ranges from current AI capabilities to speculative futures, examining both the excitement and concerns surrounding these advancements. With practical insights from business and academia, they highlight the ethical, societal, and operational implications of fast-evolving AI tech. While AGI remains a theoretical goal, today&apos;s leaders can benefit by balancing innovation with responsibility, ensuring AI deployments align with both business value and human-centered values.]]></description>
    <content:encoded><![CDATA[In Episode 49 of &apos;100 Days of Data,&apos; Jonas and Amy tackle the provocative question: will AI surpass human intelligence? They explore the concept of the technological singularity, breaking down key terms like Artificial General Intelligence (AGI) and superintelligence. The discussion ranges from current AI capabilities to speculative futures, examining both the excitement and concerns surrounding these advancements. With practical insights from business and academia, they highlight the ethical, societal, and operational implications of fast-evolving AI tech. While AGI remains a theoretical goal, today&apos;s leaders can benefit by balancing innovation with responsibility, ensuring AI deployments align with both business value and human-centered values.]]></content:encoded>
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    <pubDate>Fri, 23 Jan 2026 09:00:04 +0200</pubDate>
    <itunes:duration>442</itunes:duration>
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    <itunes:title>Episode 48 - AI &amp; Human Augmentation</itunes:title>
    <title>Episode 48 - AI &amp; Human Augmentation</title>
    <itunes:summary><![CDATA[In Episode 48 of '100 Days of Data,' Jonas and Amy explore how AI can serve as a powerful partner to humans through augmentation rather than replacement. The conversation reframes AI from a threat to a collaborator, highlighting real-world examples in healthcare, finance, retail, and manufacturing where human+machine teams outperform either alone. They discuss key concepts like cognitive load, explainability, and the 'centaur model' from chess, emphasizing the importance of designing AI syste...]]></itunes:summary>
    <description><![CDATA[In Episode 48 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI can serve as a powerful partner to humans through augmentation rather than replacement. The conversation reframes AI from a threat to a collaborator, highlighting real-world examples in healthcare, finance, retail, and manufacturing where human+machine teams outperform either alone. They discuss key concepts like cognitive load, explainability, and the &apos;centaur model&apos; from chess, emphasizing the importance of designing AI systems that enhance human judgment, not sideline it. The episode also digs into the historical roots of Augmented Intelligence and explains how organizations can drive adoption by centering human expertise in AI-powered workflows. Whether you&apos;re a business leader or curious technologist, this episode offers valuable perspective on how a collaborative AI future is not only possible but already underway.]]></description>
    <content:encoded><![CDATA[In Episode 48 of &apos;100 Days of Data,&apos; Jonas and Amy explore how AI can serve as a powerful partner to humans through augmentation rather than replacement. The conversation reframes AI from a threat to a collaborator, highlighting real-world examples in healthcare, finance, retail, and manufacturing where human+machine teams outperform either alone. They discuss key concepts like cognitive load, explainability, and the &apos;centaur model&apos; from chess, emphasizing the importance of designing AI systems that enhance human judgment, not sideline it. The episode also digs into the historical roots of Augmented Intelligence and explains how organizations can drive adoption by centering human expertise in AI-powered workflows. Whether you&apos;re a business leader or curious technologist, this episode offers valuable perspective on how a collaborative AI future is not only possible but already underway.]]></content:encoded>
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    <pubDate>Thu, 22 Jan 2026 09:00:04 +0200</pubDate>
    <itunes:duration>427</itunes:duration>
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    <itunes:title>Episode 47 - The Future of Data Infrastructure</itunes:title>
    <title>Episode 47 - The Future of Data Infrastructure</title>
    <itunes:summary><![CDATA[In Episode 47 of '100 Days of Data,' Jonas and Amy dive into the rapidly evolving landscape of data infrastructure — from the rise of edge computing to the promise of quantum technology. They explain how traditional centralized models are giving way to more distributed, agile architectures that prioritize speed, resiliency, and privacy. Real-world examples illustrate edge-enabled AI in autonomous vehicles and retail, while quantum computing is explored as a game-changing yet nascent complemen...]]></itunes:summary>
    <description><![CDATA[In Episode 47 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the rapidly evolving landscape of data infrastructure — from the rise of edge computing to the promise of quantum technology. They explain how traditional centralized models are giving way to more distributed, agile architectures that prioritize speed, resiliency, and privacy. Real-world examples illustrate edge-enabled AI in autonomous vehicles and retail, while quantum computing is explored as a game-changing yet nascent complement to existing systems. The episode emphasizes the importance of orchestration across cloud, edge, and quantum layers, as well as the need for interoperability, automation, and sustainable design. With insights from both theory and practice, this conversation helps business and tech leaders navigate the shift toward next-generation, hybrid data ecosystems.]]></description>
    <content:encoded><![CDATA[In Episode 47 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the rapidly evolving landscape of data infrastructure — from the rise of edge computing to the promise of quantum technology. They explain how traditional centralized models are giving way to more distributed, agile architectures that prioritize speed, resiliency, and privacy. Real-world examples illustrate edge-enabled AI in autonomous vehicles and retail, while quantum computing is explored as a game-changing yet nascent complement to existing systems. The episode emphasizes the importance of orchestration across cloud, edge, and quantum layers, as well as the need for interoperability, automation, and sustainable design. With insights from both theory and practice, this conversation helps business and tech leaders navigate the shift toward next-generation, hybrid data ecosystems.]]></content:encoded>
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    <pubDate>Wed, 21 Jan 2026 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 46 - AI &amp; Security</itunes:title>
    <title>Episode 46 - AI &amp; Security</title>
    <itunes:summary><![CDATA[In Episode 46 of '100 Days of Data,' Jonas and Amy explore the increasingly complex relationship between artificial intelligence and cybersecurity. They break down how AI is being weaponized through deepfakes, personalized phishing, and social engineering attacks—and how it simultaneously strengthens defenses through anomaly detection, biometric authentication, and real-time threat monitoring. Drawing from real-world examples and consulting experiences, they examine the arms race between atta...]]></itunes:summary>
    <description><![CDATA[In Episode 46 of &apos;100 Days of Data,&apos; Jonas and Amy explore the increasingly complex relationship between artificial intelligence and cybersecurity. They break down how AI is being weaponized through deepfakes, personalized phishing, and social engineering attacks—and how it simultaneously strengthens defenses through anomaly detection, biometric authentication, and real-time threat monitoring. Drawing from real-world examples and consulting experiences, they examine the arms race between attackers and defenders in the digital space. Key topics include the mechanics of deepfakes via GANs, the challenges of detection, and emerging solutions like digital watermarks and AI-enhanced threat response. With practical insights and forward-looking analysis, this episode highlights why AI security is no longer a backend issue—it’s a strategic imperative.]]></description>
    <content:encoded><![CDATA[In Episode 46 of &apos;100 Days of Data,&apos; Jonas and Amy explore the increasingly complex relationship between artificial intelligence and cybersecurity. They break down how AI is being weaponized through deepfakes, personalized phishing, and social engineering attacks—and how it simultaneously strengthens defenses through anomaly detection, biometric authentication, and real-time threat monitoring. Drawing from real-world examples and consulting experiences, they examine the arms race between attackers and defenders in the digital space. Key topics include the mechanics of deepfakes via GANs, the challenges of detection, and emerging solutions like digital watermarks and AI-enhanced threat response. With practical insights and forward-looking analysis, this episode highlights why AI security is no longer a backend issue—it’s a strategic imperative.]]></content:encoded>
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    <pubDate>Tue, 20 Jan 2026 09:00:04 +0200</pubDate>
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  <item>
    <itunes:title>Episode 45 - AI for Good</itunes:title>
    <title>Episode 45 - AI for Good</title>
    <itunes:summary><![CDATA[In Episode 45 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is increasingly being used for positive societal impact under the banner of 'AI for Good.' They delve into real-world applications across sustainability, humanitarian aid, and education—showcasing how AI models optimize energy grids, support disaster response, and personalize learning. The conversation also highlights critical considerations such as data quality, ethical AI design, and robust governance fra...]]></itunes:summary>
    <description><![CDATA[In Episode 45 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is increasingly being used for positive societal impact under the banner of &apos;AI for Good.&apos; They delve into real-world applications across sustainability, humanitarian aid, and education—showcasing how AI models optimize energy grids, support disaster response, and personalize learning. The conversation also highlights critical considerations such as data quality, ethical AI design, and robust governance frameworks to ensure long-term benefits. With examples ranging from AI-powered drones in agriculture to predictive tools aiding refugees, this episode illustrates both the promise and responsibility of applying AI to address global challenges. Whether you&apos;re a business leader, technologist, or policymaker, this episode offers key insights into aligning AI efforts with human and planetary needs.]]></description>
    <content:encoded><![CDATA[In Episode 45 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is increasingly being used for positive societal impact under the banner of &apos;AI for Good.&apos; They delve into real-world applications across sustainability, humanitarian aid, and education—showcasing how AI models optimize energy grids, support disaster response, and personalize learning. The conversation also highlights critical considerations such as data quality, ethical AI design, and robust governance frameworks to ensure long-term benefits. With examples ranging from AI-powered drones in agriculture to predictive tools aiding refugees, this episode illustrates both the promise and responsibility of applying AI to address global challenges. Whether you&apos;re a business leader, technologist, or policymaker, this episode offers key insights into aligning AI efforts with human and planetary needs.]]></content:encoded>
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    <pubDate>Mon, 19 Jan 2026 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 44 - AI &amp; Jobs</itunes:title>
    <title>Episode 44 - AI &amp; Jobs</title>
    <itunes:summary><![CDATA[In Episode 44 of '100 Days of Data,' Jonas and Amy dive into one of the most pressing questions of our time: will AI take your job or make it better? Exploring the growing role of automation, they discuss how AI is transforming not just the tasks we perform, but the very nature of work itself. From cognitive automation to the surge in reskilling initiatives, the conversation highlights real-world examples from industries like automotive, financial services, retail, and healthcare. Listeners w...]]></itunes:summary>
    <description><![CDATA[In Episode 44 of &apos;100 Days of Data,&apos; Jonas and Amy dive into one of the most pressing questions of our time: will AI take your job or make it better? Exploring the growing role of automation, they discuss how AI is transforming not just the tasks we perform, but the very nature of work itself. From cognitive automation to the surge in reskilling initiatives, the conversation highlights real-world examples from industries like automotive, financial services, retail, and healthcare. Listeners will gain insights into how AI augments human capabilities, the importance of lifelong learning, and the need for ethical and inclusive workforce transitions. Rather than painting a picture of job loss, the hosts emphasize evolution — a future where humans work alongside AI in new and dynamic roles.]]></description>
    <content:encoded><![CDATA[In Episode 44 of &apos;100 Days of Data,&apos; Jonas and Amy dive into one of the most pressing questions of our time: will AI take your job or make it better? Exploring the growing role of automation, they discuss how AI is transforming not just the tasks we perform, but the very nature of work itself. From cognitive automation to the surge in reskilling initiatives, the conversation highlights real-world examples from industries like automotive, financial services, retail, and healthcare. Listeners will gain insights into how AI augments human capabilities, the importance of lifelong learning, and the need for ethical and inclusive workforce transitions. Rather than painting a picture of job loss, the hosts emphasize evolution — a future where humans work alongside AI in new and dynamic roles.]]></content:encoded>
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    <pubDate>Fri, 16 Jan 2026 09:00:05 +0200</pubDate>
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    <itunes:title>Episode 43 - The Role of Governments</itunes:title>
    <title>Episode 43 - The Role of Governments</title>
    <itunes:summary><![CDATA[In Episode 43 of '100 Days of Data,' Jonas and Amy explore the critical role governments play in shaping the future of AI. From crafting policies and national strategies to enforcing governance frameworks, this episode examines how public institutions can promote innovation while mitigating risks such as bias, explainability, and misuse. They discuss real-world examples like the EU's AI Act and regulatory sandboxes, shedding light on how nations balance speed and caution in a rapidly evolving...]]></itunes:summary>
    <description><![CDATA[In Episode 43 of &apos;100 Days of Data,&apos; Jonas and Amy explore the critical role governments play in shaping the future of AI. From crafting policies and national strategies to enforcing governance frameworks, this episode examines how public institutions can promote innovation while mitigating risks such as bias, explainability, and misuse. They discuss real-world examples like the EU&apos;s AI Act and regulatory sandboxes, shedding light on how nations balance speed and caution in a rapidly evolving tech landscape. The conversation highlights governments not just as rule-makers but as collaborators who enable responsible AI deployment across sectors like healthcare, finance, and transportation. A must-listen for business leaders and policymakers navigating the AI frontier.]]></description>
    <content:encoded><![CDATA[In Episode 43 of &apos;100 Days of Data,&apos; Jonas and Amy explore the critical role governments play in shaping the future of AI. From crafting policies and national strategies to enforcing governance frameworks, this episode examines how public institutions can promote innovation while mitigating risks such as bias, explainability, and misuse. They discuss real-world examples like the EU&apos;s AI Act and regulatory sandboxes, shedding light on how nations balance speed and caution in a rapidly evolving tech landscape. The conversation highlights governments not just as rule-makers but as collaborators who enable responsible AI deployment across sectors like healthcare, finance, and transportation. A must-listen for business leaders and policymakers navigating the AI frontier.]]></content:encoded>
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    <pubDate>Thu, 15 Jan 2026 09:00:05 +0200</pubDate>
    <itunes:duration>455</itunes:duration>
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    <itunes:title>Episode 42 - Privacy &amp; Data Protection</itunes:title>
    <title>Episode 42 - Privacy &amp; Data Protection</title>
    <itunes:summary><![CDATA[In Episode 42 of '100 Days of Data,' Jonas and Amy explore the critical role of privacy and data protection in the era of AI. Drawing on real-world examples — from healthcare to autonomous vehicles — they illustrate how regulations like GDPR and the proposed AI Act are reshaping how organizations handle personal data. They delve into key concepts such as data minimization, data sovereignty, and encryption, while highlighting advanced techniques like differential privacy and role-based access ...]]></itunes:summary>
    <description><![CDATA[In Episode 42 of &apos;100 Days of Data,&apos; Jonas and Amy explore the critical role of privacy and data protection in the era of AI. Drawing on real-world examples — from healthcare to autonomous vehicles — they illustrate how regulations like GDPR and the proposed AI Act are reshaping how organizations handle personal data. They delve into key concepts such as data minimization, data sovereignty, and encryption, while highlighting advanced techniques like differential privacy and role-based access controls. More than just legal checkboxes, these practices are essential for building consumer trust and enabling responsible AI development. With data powering major innovations and also presenting serious risks, the episode emphasizes the importance of embedding privacy and protection throughout the entire AI lifecycle to ensure ethical and sustainable progress.]]></description>
    <content:encoded><![CDATA[In Episode 42 of &apos;100 Days of Data,&apos; Jonas and Amy explore the critical role of privacy and data protection in the era of AI. Drawing on real-world examples — from healthcare to autonomous vehicles — they illustrate how regulations like GDPR and the proposed AI Act are reshaping how organizations handle personal data. They delve into key concepts such as data minimization, data sovereignty, and encryption, while highlighting advanced techniques like differential privacy and role-based access controls. More than just legal checkboxes, these practices are essential for building consumer trust and enabling responsible AI development. With data powering major innovations and also presenting serious risks, the episode emphasizes the importance of embedding privacy and protection throughout the entire AI lifecycle to ensure ethical and sustainable progress.]]></content:encoded>
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    <pubDate>Wed, 14 Jan 2026 09:00:03 +0200</pubDate>
    <itunes:duration>465</itunes:duration>
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    <itunes:title>Episode 38 - AI in Finance</itunes:title>
    <title>Episode 38 - AI in Finance</title>
    <itunes:summary><![CDATA[In Episode 38 of '100 Days of Data,' Jonas and Amy delve into the transformative role of AI in the financial sector, exploring how it powers fast-paced trading, strengthens fraud detection, and enables personalized financial services. The hosts explain how machine learning and reinforcement learning fuel high-frequency trading systems, identify suspicious activities, and personalize credit and investment recommendations. Real-world examples—from robo-advisors to adaptive fraud models—highligh...]]></itunes:summary>
    <description><![CDATA[In Episode 38 of &apos;100 Days of Data,&apos; Jonas and Amy delve into the transformative role of AI in the financial sector, exploring how it powers fast-paced trading, strengthens fraud detection, and enables personalized financial services. The hosts explain how machine learning and reinforcement learning fuel high-frequency trading systems, identify suspicious activities, and personalize credit and investment recommendations. Real-world examples—from robo-advisors to adaptive fraud models—highlight AI’s impact at every layer of finance. But with great power comes great responsibility: the episode also addresses the need for transparency, ethical considerations, and ongoing oversight to ensure AI systems remain fair, accurate, and trusted in high-stakes financial environments. Whether you’re curious about market prediction or better banking through algorithms, this episode provides practical insights into how data-driven intelligence is quietly reshaping where, how, and why money moves.]]></description>
    <content:encoded><![CDATA[In Episode 38 of &apos;100 Days of Data,&apos; Jonas and Amy delve into the transformative role of AI in the financial sector, exploring how it powers fast-paced trading, strengthens fraud detection, and enables personalized financial services. The hosts explain how machine learning and reinforcement learning fuel high-frequency trading systems, identify suspicious activities, and personalize credit and investment recommendations. Real-world examples—from robo-advisors to adaptive fraud models—highlight AI’s impact at every layer of finance. But with great power comes great responsibility: the episode also addresses the need for transparency, ethical considerations, and ongoing oversight to ensure AI systems remain fair, accurate, and trusted in high-stakes financial environments. Whether you’re curious about market prediction or better banking through algorithms, this episode provides practical insights into how data-driven intelligence is quietly reshaping where, how, and why money moves.]]></content:encoded>
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    <pubDate>Wed, 07 Jan 2026 11:06:00 +0200</pubDate>
    <itunes:duration>433</itunes:duration>
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    <itunes:title>Episode 41 - Ethics of AI</itunes:title>
    <title>Episode 41 - Ethics of AI</title>
    <itunes:summary><![CDATA[In Episode 41 of '100 Days of Data,' Jonas and Amy tackle the critical topic of AI ethics with a compelling opening: 'Just because we can doesn’t mean we should.' Together, they explore how fairness, accountability, and transparency form the ethical backbone of responsible AI systems. Through real-world stories—from biased loan approvals to opaque patient triage systems—they illustrate how ethical missteps in AI design and deployment can lead to serious social and business consequences. The e...]]></itunes:summary>
    <description><![CDATA[In Episode 41 of &apos;100 Days of Data,&apos; Jonas and Amy tackle the critical topic of AI ethics with a compelling opening: &apos;Just because we can doesn’t mean we should.&apos; Together, they explore how fairness, accountability, and transparency form the ethical backbone of responsible AI systems. Through real-world stories—from biased loan approvals to opaque patient triage systems—they illustrate how ethical missteps in AI design and deployment can lead to serious social and business consequences. The episode highlights why ethical considerations shouldn&apos;t be an afterthought, but instead an integral part of AI development from day one. With insights from industry and academia, Jonas and Amy explain how ethical AI isn&apos;t just the right thing—it&apos;s also smart business. It&apos;s a must-listen for anyone building or managing AI solutions, particularly as technology races ahead of regulation.]]></description>
    <content:encoded><![CDATA[In Episode 41 of &apos;100 Days of Data,&apos; Jonas and Amy tackle the critical topic of AI ethics with a compelling opening: &apos;Just because we can doesn’t mean we should.&apos; Together, they explore how fairness, accountability, and transparency form the ethical backbone of responsible AI systems. Through real-world stories—from biased loan approvals to opaque patient triage systems—they illustrate how ethical missteps in AI design and deployment can lead to serious social and business consequences. The episode highlights why ethical considerations shouldn&apos;t be an afterthought, but instead an integral part of AI development from day one. With insights from industry and academia, Jonas and Amy explain how ethical AI isn&apos;t just the right thing—it&apos;s also smart business. It&apos;s a must-listen for anyone building or managing AI solutions, particularly as technology races ahead of regulation.]]></content:encoded>
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    <pubDate>Wed, 31 Dec 2025 09:00:04 +0200</pubDate>
    <itunes:duration>428</itunes:duration>
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    <itunes:title>Episode 40 - Generative AI</itunes:title>
    <title>Episode 40 - Generative AI</title>
    <itunes:summary><![CDATA[In Episode 40 of '100 Days of Data,' Jonas and Amy dive into the fast-evolving world of generative AI and its transformative impact on content creation. They explain how models like GPT-4 and DALL·E use massive datasets and transformer architectures to generate human-like text and visuals. The discussion covers both the capabilities and limitations of generative AI, from customer service automation to creative product design. Listeners will learn how these tools are revolutionizing industries...]]></itunes:summary>
    <description><![CDATA[In Episode 40 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the fast-evolving world of generative AI and its transformative impact on content creation. They explain how models like GPT-4 and DALL·E use massive datasets and transformer architectures to generate human-like text and visuals. The discussion covers both the capabilities and limitations of generative AI, from customer service automation to creative product design. Listeners will learn how these tools are revolutionizing industries by scaling creativity and productivity—when paired with responsible human oversight. With practical examples from marketing, healthcare, and automotive sectors, this episode provides a clear, accessible look at how generative AI goes beyond analysis to invent entirely new outputs.]]></description>
    <content:encoded><![CDATA[In Episode 40 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the fast-evolving world of generative AI and its transformative impact on content creation. They explain how models like GPT-4 and DALL·E use massive datasets and transformer architectures to generate human-like text and visuals. The discussion covers both the capabilities and limitations of generative AI, from customer service automation to creative product design. Listeners will learn how these tools are revolutionizing industries by scaling creativity and productivity—when paired with responsible human oversight. With practical examples from marketing, healthcare, and automotive sectors, this episode provides a clear, accessible look at how generative AI goes beyond analysis to invent entirely new outputs.]]></content:encoded>
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    <pubDate>Tue, 30 Dec 2025 09:00:04 +0200</pubDate>
    <itunes:duration>420</itunes:duration>
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    <itunes:title>Episode 39 - AI in Retail &amp; Marketing</itunes:title>
    <title>Episode 39 - AI in Retail &amp; Marketing</title>
    <itunes:summary><![CDATA[In Episode 39 of '100 Days of Data,' Jonas and Amy dive into the powerful role of AI in retail and marketing, revealing how your shopping cart might know you better than you do. They explore how recommendation systems work using collaborative and content-based filtering, and how businesses are creating hybrid solutions to drive sales. The episode also unpacks the nuances of personalization—beyond just product suggestions—and the strategic use of AI in customer segmentation and loyalty program...]]></itunes:summary>
    <description><![CDATA[In Episode 39 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the powerful role of AI in retail and marketing, revealing how your shopping cart might know you better than you do. They explore how recommendation systems work using collaborative and content-based filtering, and how businesses are creating hybrid solutions to drive sales. The episode also unpacks the nuances of personalization—beyond just product suggestions—and the strategic use of AI in customer segmentation and loyalty programs. Practical stories from real businesses illustrate how personalized emails and smart coupons can significantly boost engagement and revenue. Privacy isn’t left out; the hosts discuss how techniques like federated learning are keeping customer data secure while still enabling tailored experiences. Whether you&apos;re in tech or retail, this episode shows how AI is reshaping how businesses connect with customers.]]></description>
    <content:encoded><![CDATA[In Episode 39 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the powerful role of AI in retail and marketing, revealing how your shopping cart might know you better than you do. They explore how recommendation systems work using collaborative and content-based filtering, and how businesses are creating hybrid solutions to drive sales. The episode also unpacks the nuances of personalization—beyond just product suggestions—and the strategic use of AI in customer segmentation and loyalty programs. Practical stories from real businesses illustrate how personalized emails and smart coupons can significantly boost engagement and revenue. Privacy isn’t left out; the hosts discuss how techniques like federated learning are keeping customer data secure while still enabling tailored experiences. Whether you&apos;re in tech or retail, this episode shows how AI is reshaping how businesses connect with customers.]]></content:encoded>
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    <pubDate>Mon, 29 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 37 - AI in Automotive</itunes:title>
    <title>Episode 37 - AI in Automotive</title>
    <itunes:summary><![CDATA[In Episode 37 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is revolutionizing the automotive industry. From autonomous driving systems that mimic human reasoning to predictive maintenance that minimizes vehicle downtime, AI is transforming both how our cars operate and how we move through cities. The hosts break down complex topics like sensor fusion, real-time decision-making, and the progression from assisted driving to full autonomy. They also highlight real-wor...]]></itunes:summary>
    <description><![CDATA[In Episode 37 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is revolutionizing the automotive industry. From autonomous driving systems that mimic human reasoning to predictive maintenance that minimizes vehicle downtime, AI is transforming both how our cars operate and how we move through cities. The hosts break down complex topics like sensor fusion, real-time decision-making, and the progression from assisted driving to full autonomy. They also highlight real-world applications from Tesla and Waymo, alongside smart city initiatives optimizing traffic flow. Challenges like safety, ethics, and regulations are discussed, emphasizing the need for trustworthy and adaptable AI systems. This episode offers both theoretical insights and practical examples, making it a must-listen for professionals across transportation, AI, and data science sectors.]]></description>
    <content:encoded><![CDATA[In Episode 37 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is revolutionizing the automotive industry. From autonomous driving systems that mimic human reasoning to predictive maintenance that minimizes vehicle downtime, AI is transforming both how our cars operate and how we move through cities. The hosts break down complex topics like sensor fusion, real-time decision-making, and the progression from assisted driving to full autonomy. They also highlight real-world applications from Tesla and Waymo, alongside smart city initiatives optimizing traffic flow. Challenges like safety, ethics, and regulations are discussed, emphasizing the need for trustworthy and adaptable AI systems. This episode offers both theoretical insights and practical examples, making it a must-listen for professionals across transportation, AI, and data science sectors.]]></content:encoded>
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    <pubDate>Thu, 25 Dec 2025 11:34:30 +0200</pubDate>
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    <itunes:title>Episode 36 - AI in Healthcare</itunes:title>
    <title>Episode 36 - AI in Healthcare</title>
    <itunes:summary><![CDATA[In Episode 36 of '100 Days of Data,' Jonas and Amy explore how artificial intelligence is transforming healthcare — from flagging early signs of disease to accelerating the drug discovery process. They explain how AI helps clinicians make more accurate diagnoses, personalize treatments, and monitor patients in real time. Real-world examples showcase AI’s role in improving efficiency, enhancing decision-making, and ultimately saving lives. The discussion also covers the complexity of healthcar...]]></itunes:summary>
    <description><![CDATA[In Episode 36 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is transforming healthcare — from flagging early signs of disease to accelerating the drug discovery process. They explain how AI helps clinicians make more accurate diagnoses, personalize treatments, and monitor patients in real time. Real-world examples showcase AI’s role in improving efficiency, enhancing decision-making, and ultimately saving lives. The discussion also covers the complexity of healthcare data, the importance of explainable AI, and safeguards like federated learning to protect patient privacy. Listeners will gain insights into how thoughtful integration of AI supports doctors, not replaces them, and how ethical and inclusive design is critical for equitable care. This episode shines a spotlight on the intersection of advanced technology, human expertise, and compassionate care — offering a glimpse into the future of medicine driven by data.]]></description>
    <content:encoded><![CDATA[In Episode 36 of &apos;100 Days of Data,&apos; Jonas and Amy explore how artificial intelligence is transforming healthcare — from flagging early signs of disease to accelerating the drug discovery process. They explain how AI helps clinicians make more accurate diagnoses, personalize treatments, and monitor patients in real time. Real-world examples showcase AI’s role in improving efficiency, enhancing decision-making, and ultimately saving lives. The discussion also covers the complexity of healthcare data, the importance of explainable AI, and safeguards like federated learning to protect patient privacy. Listeners will gain insights into how thoughtful integration of AI supports doctors, not replaces them, and how ethical and inclusive design is critical for equitable care. This episode shines a spotlight on the intersection of advanced technology, human expertise, and compassionate care — offering a glimpse into the future of medicine driven by data.]]></content:encoded>
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    <pubDate>Mon, 22 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 35 - Explainable AI</itunes:title>
    <title>Episode 35 - Explainable AI</title>
    <itunes:summary><![CDATA[In Episode 35 of '100 Days of Data,' Jonas and Amy explore the essential role of explainable AI (XAI) in building trust and transparency in AI-driven systems. From real-world scenarios in finance and healthcare to technical strategies like intrinsic vs. post-hoc explainability, they dive into how organizations can make AI decisions understandable and accountable. The discussion covers key concepts—interpretability, transparency, and accountability—and highlights the risks of deploying 'black ...]]></itunes:summary>
    <description><![CDATA[In Episode 35 of &apos;100 Days of Data,&apos; Jonas and Amy explore the essential role of explainable AI (XAI) in building trust and transparency in AI-driven systems. From real-world scenarios in finance and healthcare to technical strategies like intrinsic vs. post-hoc explainability, they dive into how organizations can make AI decisions understandable and accountable. The discussion covers key concepts—interpretability, transparency, and accountability—and highlights the risks of deploying &apos;black box&apos; models without clear explanations. With vivid analogies and field-tested stories, this episode emphasizes why making AI explainable isn&apos;t just a technical goal—it&apos;s a business, ethical, and regulatory imperative.]]></description>
    <content:encoded><![CDATA[In Episode 35 of &apos;100 Days of Data,&apos; Jonas and Amy explore the essential role of explainable AI (XAI) in building trust and transparency in AI-driven systems. From real-world scenarios in finance and healthcare to technical strategies like intrinsic vs. post-hoc explainability, they dive into how organizations can make AI decisions understandable and accountable. The discussion covers key concepts—interpretability, transparency, and accountability—and highlights the risks of deploying &apos;black box&apos; models without clear explanations. With vivid analogies and field-tested stories, this episode emphasizes why making AI explainable isn&apos;t just a technical goal—it&apos;s a business, ethical, and regulatory imperative.]]></content:encoded>
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    <pubDate>Fri, 19 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 34 - Bias in AI</itunes:title>
    <title>Episode 34 - Bias in AI</title>
    <itunes:summary><![CDATA[In Episode 34 of '100 Days of Data,' hosts Jonas and Amy dive into the complex issue of bias in AI. They explore how algorithms can inherit societal prejudices through skewed data, flawed design choices, and unmonitored deployment. Through real-world examples from healthcare, finance, and insurance, they demonstrate the serious impact biased models can have on people’s lives — from unequal loan approvals to racial disparities in medical care. The duo discusses fairness as a multifaceted goal ...]]></itunes:summary>
    <description><![CDATA[In Episode 34 of &apos;100 Days of Data,&apos; hosts Jonas and Amy dive into the complex issue of bias in AI. They explore how algorithms can inherit societal prejudices through skewed data, flawed design choices, and unmonitored deployment. Through real-world examples from healthcare, finance, and insurance, they demonstrate the serious impact biased models can have on people’s lives — from unequal loan approvals to racial disparities in medical care. The duo discusses fairness as a multifaceted goal in AI, the challenges of achieving it, and practical tools like bias mitigation techniques and explainability frameworks. They emphasize that addressing bias is not just a technical challenge but a social responsibility involving diverse teams, continual monitoring, and transparency. Tune in for an essential conversation about making AI systems more just and trustworthy in real-world applications.]]></description>
    <content:encoded><![CDATA[In Episode 34 of &apos;100 Days of Data,&apos; hosts Jonas and Amy dive into the complex issue of bias in AI. They explore how algorithms can inherit societal prejudices through skewed data, flawed design choices, and unmonitored deployment. Through real-world examples from healthcare, finance, and insurance, they demonstrate the serious impact biased models can have on people’s lives — from unequal loan approvals to racial disparities in medical care. The duo discusses fairness as a multifaceted goal in AI, the challenges of achieving it, and practical tools like bias mitigation techniques and explainability frameworks. They emphasize that addressing bias is not just a technical challenge but a social responsibility involving diverse teams, continual monitoring, and transparency. Tune in for an essential conversation about making AI systems more just and trustworthy in real-world applications.]]></content:encoded>
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    <pubDate>Thu, 18 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 33 - Overfitting &amp; Underfitting</itunes:title>
    <title>Episode 33 - Overfitting &amp; Underfitting</title>
    <itunes:summary><![CDATA[In Episode 33 of '100 Days of Data,' Jonas and Amy dive deep into the critical concepts of overfitting and underfitting in AI models. Using relatable analogies and real-world examples—from predictive maintenance to customer churn—they explain how models can be too simplistic or overly complex, both of which hurt performance. The discussion introduces key concepts like generalization, bias, and variance, emphasizing that the goal is to find the right balance for your model to perform well on n...]]></itunes:summary>
    <description><![CDATA[In Episode 33 of &apos;100 Days of Data,&apos; Jonas and Amy dive deep into the critical concepts of overfitting and underfitting in AI models. Using relatable analogies and real-world examples—from predictive maintenance to customer churn—they explain how models can be too simplistic or overly complex, both of which hurt performance. The discussion introduces key concepts like generalization, bias, and variance, emphasizing that the goal is to find the right balance for your model to perform well on new, unseen data. They explore practical approaches such as regularization, cross-validation, and appropriate model selection to manage complexity. Whether you&apos;re a data scientist or business leader, this episode offers valuable insights on how to spot and fix model performance issues before they impact outcomes.]]></description>
    <content:encoded><![CDATA[In Episode 33 of &apos;100 Days of Data,&apos; Jonas and Amy dive deep into the critical concepts of overfitting and underfitting in AI models. Using relatable analogies and real-world examples—from predictive maintenance to customer churn—they explain how models can be too simplistic or overly complex, both of which hurt performance. The discussion introduces key concepts like generalization, bias, and variance, emphasizing that the goal is to find the right balance for your model to perform well on new, unseen data. They explore practical approaches such as regularization, cross-validation, and appropriate model selection to manage complexity. Whether you&apos;re a data scientist or business leader, this episode offers valuable insights on how to spot and fix model performance issues before they impact outcomes.]]></content:encoded>
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    <pubDate>Wed, 17 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 32 - Model Training &amp; Testing</itunes:title>
    <title>Episode 32 - Model Training &amp; Testing</title>
    <itunes:summary><![CDATA[In Episode 32 of '100 Days of Data,' Jonas and Amy compare model training to an athlete’s workout routine, emphasizing the critical roles of training, validation, and testing datasets in building reliable AI models. They unpack the function of each data split: the training set teaches the model, the validation set fine-tunes it, and the testing set evaluates its real-world performance. Drawing from industry examples in healthcare, finance, retail, and automotive, they illustrate how improper ...]]></itunes:summary>
    <description><![CDATA[In Episode 32 of &apos;100 Days of Data,&apos; Jonas and Amy compare model training to an athlete’s workout routine, emphasizing the critical roles of training, validation, and testing datasets in building reliable AI models. They unpack the function of each data split: the training set teaches the model, the validation set fine-tunes it, and the testing set evaluates its real-world performance. Drawing from industry examples in healthcare, finance, retail, and automotive, they illustrate how improper use—or neglect—of these splits can lead to misleading results and failed deployments. The conversation also introduces techniques like cross-validation to handle small datasets and discusses the importance of transparency and documentation to gain stakeholder trust. This episode bridges foundational AI concepts with practical implementation, empowering listeners to build smarter, more trustworthy models.]]></description>
    <content:encoded><![CDATA[In Episode 32 of &apos;100 Days of Data,&apos; Jonas and Amy compare model training to an athlete’s workout routine, emphasizing the critical roles of training, validation, and testing datasets in building reliable AI models. They unpack the function of each data split: the training set teaches the model, the validation set fine-tunes it, and the testing set evaluates its real-world performance. Drawing from industry examples in healthcare, finance, retail, and automotive, they illustrate how improper use—or neglect—of these splits can lead to misleading results and failed deployments. The conversation also introduces techniques like cross-validation to handle small datasets and discusses the importance of transparency and documentation to gain stakeholder trust. This episode bridges foundational AI concepts with practical implementation, empowering listeners to build smarter, more trustworthy models.]]></content:encoded>
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    <pubDate>Tue, 16 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 31 - Data Preparation for AI</itunes:title>
    <title>Episode 31 - Data Preparation for AI</title>
    <itunes:summary><![CDATA[In Episode 31 of '100 Days of Data,' titled 'Data Preparation for AI,' Jonas and Amy explore why up to 80% of AI work revolves around data cleaning, preprocessing, and feature engineering. They break down these critical steps in transforming raw, messy data into structured formats ready for modeling. From handling missing values and duplicates to encoding categories and scaling features, the hosts blend theory with vivid real-world examples—including use cases in automotive, retail, logistics...]]></itunes:summary>
    <description><![CDATA[In Episode 31 of &apos;100 Days of Data,&apos; titled &apos;Data Preparation for AI,&apos; Jonas and Amy explore why up to 80% of AI work revolves around data cleaning, preprocessing, and feature engineering. They break down these critical steps in transforming raw, messy data into structured formats ready for modeling. From handling missing values and duplicates to encoding categories and scaling features, the hosts blend theory with vivid real-world examples—including use cases in automotive, retail, logistics, and healthcare. Listeners also learn how effective feature engineering combines creativity and domain knowledge to boost model performance. Whether you&apos;re building AI applications or advising businesses, this episode provides a clear roadmap to data preparation as the foundation of trustworthy, high-impact AI systems.]]></description>
    <content:encoded><![CDATA[In Episode 31 of &apos;100 Days of Data,&apos; titled &apos;Data Preparation for AI,&apos; Jonas and Amy explore why up to 80% of AI work revolves around data cleaning, preprocessing, and feature engineering. They break down these critical steps in transforming raw, messy data into structured formats ready for modeling. From handling missing values and duplicates to encoding categories and scaling features, the hosts blend theory with vivid real-world examples—including use cases in automotive, retail, logistics, and healthcare. Listeners also learn how effective feature engineering combines creativity and domain knowledge to boost model performance. Whether you&apos;re building AI applications or advising businesses, this episode provides a clear roadmap to data preparation as the foundation of trustworthy, high-impact AI systems.]]></content:encoded>
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    <pubDate>Mon, 15 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 30 - AI vs Traditional Programming</itunes:title>
    <title>Episode 30 - AI vs Traditional Programming</title>
    <itunes:summary><![CDATA[In Episode 30 of '100 Days of Data,' Jonas and Amy explore the foundational shift from traditional programming to AI-driven development. They contrast the rule-based methods of classical programming with the data-driven learning approach of AI, particularly machine learning. The episode highlights how AI enables systems to adapt and evolve using large datasets, making it ideal for complex, variable environments like voice recognition, predictive maintenance, and personalized recommendations. ...]]></itunes:summary>
    <description><![CDATA[In Episode 30 of &apos;100 Days of Data,&apos; Jonas and Amy explore the foundational shift from traditional programming to AI-driven development. They contrast the rule-based methods of classical programming with the data-driven learning approach of AI, particularly machine learning. The episode highlights how AI enables systems to adapt and evolve using large datasets, making it ideal for complex, variable environments like voice recognition, predictive maintenance, and personalized recommendations. They emphasize the paradigm shift not only in technology, but also in mindset and skillset—moving from writing explicit rules to curating quality data for model training. Through real-world examples from retail, manufacturing, and healthcare, listeners gain practical insights into when to use AI, when to stick with traditional coding, and how hybrid systems combine the best of both worlds.]]></description>
    <content:encoded><![CDATA[In Episode 30 of &apos;100 Days of Data,&apos; Jonas and Amy explore the foundational shift from traditional programming to AI-driven development. They contrast the rule-based methods of classical programming with the data-driven learning approach of AI, particularly machine learning. The episode highlights how AI enables systems to adapt and evolve using large datasets, making it ideal for complex, variable environments like voice recognition, predictive maintenance, and personalized recommendations. They emphasize the paradigm shift not only in technology, but also in mindset and skillset—moving from writing explicit rules to curating quality data for model training. Through real-world examples from retail, manufacturing, and healthcare, listeners gain practical insights into when to use AI, when to stick with traditional coding, and how hybrid systems combine the best of both worlds.]]></content:encoded>
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    <pubDate>Fri, 12 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 29 - Computer Vision</itunes:title>
    <title>Episode 29 - Computer Vision</title>
    <itunes:summary><![CDATA[Episode 29 of '100 Days of Data' dives into the world of computer vision—how machines learn to 'see' and interpret images like humans. Jonas and Amy explore the fundamentals of transforming pixels into patterns using convolutional neural networks (CNNs), discuss real-world industry use cases, and highlight the importance of robust training data. They also touch on emerging models like Vision Transformers, the difference between recognition and detection, and the challenges of adversarial exam...]]></itunes:summary>
    <description><![CDATA[Episode 29 of &apos;100 Days of Data&apos; dives into the world of computer vision—how machines learn to &apos;see&apos; and interpret images like humans. Jonas and Amy explore the fundamentals of transforming pixels into patterns using convolutional neural networks (CNNs), discuss real-world industry use cases, and highlight the importance of robust training data. They also touch on emerging models like Vision Transformers, the difference between recognition and detection, and the challenges of adversarial examples. With insights from manufacturing, retail, and healthcare, this episode offers both technical foundations and business applications for leaders and practitioners looking to harness the power of visual AI.]]></description>
    <content:encoded><![CDATA[Episode 29 of &apos;100 Days of Data&apos; dives into the world of computer vision—how machines learn to &apos;see&apos; and interpret images like humans. Jonas and Amy explore the fundamentals of transforming pixels into patterns using convolutional neural networks (CNNs), discuss real-world industry use cases, and highlight the importance of robust training data. They also touch on emerging models like Vision Transformers, the difference between recognition and detection, and the challenges of adversarial examples. With insights from manufacturing, retail, and healthcare, this episode offers both technical foundations and business applications for leaders and practitioners looking to harness the power of visual AI.]]></content:encoded>
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    <pubDate>Thu, 11 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 28 - Natural Language Processing</itunes:title>
    <title>Episode 28 - Natural Language Processing</title>
    <itunes:summary><![CDATA[In Episode 28 of '100 Days of Data,' Jonas and Amy explore how machines interpret human language through Natural Language Processing (NLP). They unpack the evolution from rule-based systems to modern techniques like deep learning and transformers, and introduce key concepts like embeddings, sentiment analysis, and named entity recognition. The duo shares real-world applications—from automating customer support to improving doctor workflows—and address critical challenges, including bias and c...]]></itunes:summary>
    <description><![CDATA[In Episode 28 of &apos;100 Days of Data,&apos; Jonas and Amy explore how machines interpret human language through Natural Language Processing (NLP). They unpack the evolution from rule-based systems to modern techniques like deep learning and transformers, and introduce key concepts like embeddings, sentiment analysis, and named entity recognition. The duo shares real-world applications—from automating customer support to improving doctor workflows—and address critical challenges, including bias and context limitations. They also offer strategic advice for business leaders looking to implement NLP, emphasizing clear goals and mindful adoption. Whether you&apos;re curious about how chatbots work or how language insights can drive product decisions, this episode provides a clear, practical foundation in one of AI&apos;s most dynamic fields.]]></description>
    <content:encoded><![CDATA[In Episode 28 of &apos;100 Days of Data,&apos; Jonas and Amy explore how machines interpret human language through Natural Language Processing (NLP). They unpack the evolution from rule-based systems to modern techniques like deep learning and transformers, and introduce key concepts like embeddings, sentiment analysis, and named entity recognition. The duo shares real-world applications—from automating customer support to improving doctor workflows—and address critical challenges, including bias and context limitations. They also offer strategic advice for business leaders looking to implement NLP, emphasizing clear goals and mindful adoption. Whether you&apos;re curious about how chatbots work or how language insights can drive product decisions, this episode provides a clear, practical foundation in one of AI&apos;s most dynamic fields.]]></content:encoded>
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    <pubDate>Wed, 10 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 27 - Neural Networks</itunes:title>
    <title>Episode 27 - Neural Networks</title>
    <itunes:summary><![CDATA[In Episode 27 of '100 Days of Data,' Jonas and Amy decode the fascinating world of neural networks — AI models inspired by the structure of the human brain. Listeners will learn how artificial neurons, layers, and weights work together to recognize complex patterns in data, enabling everything from facial recognition to fraud detection. The hosts explore key neural network types like CNNs for image analysis and RNNs for sequence data, while also addressing challenges like data requirements an...]]></itunes:summary>
    <description><![CDATA[In Episode 27 of &apos;100 Days of Data,&apos; Jonas and Amy decode the fascinating world of neural networks — AI models inspired by the structure of the human brain. Listeners will learn how artificial neurons, layers, and weights work together to recognize complex patterns in data, enabling everything from facial recognition to fraud detection. The hosts explore key neural network types like CNNs for image analysis and RNNs for sequence data, while also addressing challenges like data requirements and interpretability. Real-world examples illustrate how businesses can benefit through practical strategies like transfer learning. If you&apos;ve ever wondered how AI “thinks,” this episode offers a clear, approachable introduction to one of AI’s most powerful tools.]]></description>
    <content:encoded><![CDATA[In Episode 27 of &apos;100 Days of Data,&apos; Jonas and Amy decode the fascinating world of neural networks — AI models inspired by the structure of the human brain. Listeners will learn how artificial neurons, layers, and weights work together to recognize complex patterns in data, enabling everything from facial recognition to fraud detection. The hosts explore key neural network types like CNNs for image analysis and RNNs for sequence data, while also addressing challenges like data requirements and interpretability. Real-world examples illustrate how businesses can benefit through practical strategies like transfer learning. If you&apos;ve ever wondered how AI “thinks,” this episode offers a clear, approachable introduction to one of AI’s most powerful tools.]]></content:encoded>
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    <pubDate>Tue, 09 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 26 - Reinforcement Learning</itunes:title>
    <title>Episode 26 - Reinforcement Learning</title>
    <itunes:summary><![CDATA[In Episode 26 of '100 Days of Data,' Jonas and Amy dive into the world of Reinforcement Learning (RL), likening it to training a dog—with rewards, penalties, and lots of trial and error. They explain how AI agents learn by interacting with environments, adjusting their actions to maximize rewards over time. The discussion covers core RL concepts like agents, states, actions, policies, exploration vs. exploitation, and value functions. Real-world examples include AlphaGo, autonomous vehicles, ...]]></itunes:summary>
    <description><![CDATA[In Episode 26 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of Reinforcement Learning (RL), likening it to training a dog—with rewards, penalties, and lots of trial and error. They explain how AI agents learn by interacting with environments, adjusting their actions to maximize rewards over time. The discussion covers core RL concepts like agents, states, actions, policies, exploration vs. exploitation, and value functions. Real-world examples include AlphaGo, autonomous vehicles, finance, and personalized healthcare. The hosts also touch on key challenges such as reward design, safety constraints, and the extensive data needs RL systems face. Whether you&apos;re new to AI or need a refresher, this episode offers practical insights and a relatable introduction to one of the most exciting areas in machine learning today.]]></description>
    <content:encoded><![CDATA[In Episode 26 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of Reinforcement Learning (RL), likening it to training a dog—with rewards, penalties, and lots of trial and error. They explain how AI agents learn by interacting with environments, adjusting their actions to maximize rewards over time. The discussion covers core RL concepts like agents, states, actions, policies, exploration vs. exploitation, and value functions. Real-world examples include AlphaGo, autonomous vehicles, finance, and personalized healthcare. The hosts also touch on key challenges such as reward design, safety constraints, and the extensive data needs RL systems face. Whether you&apos;re new to AI or need a refresher, this episode offers practical insights and a relatable introduction to one of the most exciting areas in machine learning today.]]></content:encoded>
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    <pubDate>Mon, 08 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 25 - Unsupervised Learning</itunes:title>
    <title>Episode 25 - Unsupervised Learning</title>
    <itunes:summary><![CDATA[In Episode 25 of '100 Days of Data,' Jonas and Amy unpack the fundamentals of unsupervised learning, a branch of machine learning where algorithms find structure in unlabeled data. They explore key techniques like clustering and dimensionality reduction, illustrating their real-world applications in customer segmentation, fraud detection, and genetic research. With relatable examples from retail, finance, and healthcare, the hosts show how unsupervised learning empowers AI to uncover patterns...]]></itunes:summary>
    <description><![CDATA[In Episode 25 of &apos;100 Days of Data,&apos; Jonas and Amy unpack the fundamentals of unsupervised learning, a branch of machine learning where algorithms find structure in unlabeled data. They explore key techniques like clustering and dimensionality reduction, illustrating their real-world applications in customer segmentation, fraud detection, and genetic research. With relatable examples from retail, finance, and healthcare, the hosts show how unsupervised learning empowers AI to uncover patterns that humans may overlook. They also discuss common algorithms such as k-means and PCA, along with the importance of domain expertise in interpreting results. The episode emphasizes how unsupervised learning&apos;s exploratory nature opens new doors for businesses dealing with complex, unlabeled datasets.]]></description>
    <content:encoded><![CDATA[In Episode 25 of &apos;100 Days of Data,&apos; Jonas and Amy unpack the fundamentals of unsupervised learning, a branch of machine learning where algorithms find structure in unlabeled data. They explore key techniques like clustering and dimensionality reduction, illustrating their real-world applications in customer segmentation, fraud detection, and genetic research. With relatable examples from retail, finance, and healthcare, the hosts show how unsupervised learning empowers AI to uncover patterns that humans may overlook. They also discuss common algorithms such as k-means and PCA, along with the importance of domain expertise in interpreting results. The episode emphasizes how unsupervised learning&apos;s exploratory nature opens new doors for businesses dealing with complex, unlabeled datasets.]]></content:encoded>
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    <pubDate>Fri, 05 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 24 - Supervised Learning</itunes:title>
    <title>Episode 24 - Supervised Learning</title>
    <itunes:summary><![CDATA[In Episode 24 of '100 Days of Data,' hosts Jonas and Amy dive deep into supervised learning, a foundational concept in machine learning where models are trained using labeled examples. They explore how labels act as the 'answer key' that helps algorithms make predictions — from classifying emails as spam to predicting house prices. The episode breaks down the two main types of supervised learning tasks: classification and regression, and highlights real-world applications in industries like h...]]></itunes:summary>
    <description><![CDATA[In Episode 24 of &apos;100 Days of Data,&apos; hosts Jonas and Amy dive deep into supervised learning, a foundational concept in machine learning where models are trained using labeled examples. They explore how labels act as the &apos;answer key&apos; that helps algorithms make predictions — from classifying emails as spam to predicting house prices. The episode breaks down the two main types of supervised learning tasks: classification and regression, and highlights real-world applications in industries like healthcare, automotive, and manufacturing. Jonas emphasizes the importance of data quality, while Amy shares insights into the practical challenges businesses face when labeling data. The discussion also touches on model evaluation metrics and common misunderstandings, such as equating machine learning with full automation. Whether you&apos;re in AI or just curious, this episode offers a clear, approachable guide to a key component of intelligent systems.]]></description>
    <content:encoded><![CDATA[In Episode 24 of &apos;100 Days of Data,&apos; hosts Jonas and Amy dive deep into supervised learning, a foundational concept in machine learning where models are trained using labeled examples. They explore how labels act as the &apos;answer key&apos; that helps algorithms make predictions — from classifying emails as spam to predicting house prices. The episode breaks down the two main types of supervised learning tasks: classification and regression, and highlights real-world applications in industries like healthcare, automotive, and manufacturing. Jonas emphasizes the importance of data quality, while Amy shares insights into the practical challenges businesses face when labeling data. The discussion also touches on model evaluation metrics and common misunderstandings, such as equating machine learning with full automation. Whether you&apos;re in AI or just curious, this episode offers a clear, approachable guide to a key component of intelligent systems.]]></content:encoded>
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    <pubDate>Thu, 04 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 23 - Machine Learning Basics</itunes:title>
    <title>Episode 23 - Machine Learning Basics</title>
    <itunes:summary><![CDATA[In Episode 23 of '100 Days of Data,' Jonas and Amy explore the fundamentals of machine learning—how machines learn patterns from data without being explicitly programmed. They break down key components including algorithms, patterns, and models, using real-world analogies and business examples to demystify complex concepts. From manufacturing defect detection to retail recommendation systems, the hosts illustrate how machine learning moves beyond traditional programming by leveraging vast amo...]]></itunes:summary>
    <description><![CDATA[In Episode 23 of &apos;100 Days of Data,&apos; Jonas and Amy explore the fundamentals of machine learning—how machines learn patterns from data without being explicitly programmed. They break down key components including algorithms, patterns, and models, using real-world analogies and business examples to demystify complex concepts. From manufacturing defect detection to retail recommendation systems, the hosts illustrate how machine learning moves beyond traditional programming by leveraging vast amounts of data. They also discuss different algorithm types, the importance of quality data, and practical challenges like balancing accuracy and interpretability. This episode serves as a solid foundation for understanding how machine learning works and why it’s revolutionizing industries big and small.]]></description>
    <content:encoded><![CDATA[In Episode 23 of &apos;100 Days of Data,&apos; Jonas and Amy explore the fundamentals of machine learning—how machines learn patterns from data without being explicitly programmed. They break down key components including algorithms, patterns, and models, using real-world analogies and business examples to demystify complex concepts. From manufacturing defect detection to retail recommendation systems, the hosts illustrate how machine learning moves beyond traditional programming by leveraging vast amounts of data. They also discuss different algorithm types, the importance of quality data, and practical challenges like balancing accuracy and interpretability. This episode serves as a solid foundation for understanding how machine learning works and why it’s revolutionizing industries big and small.]]></content:encoded>
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    <pubDate>Wed, 03 Dec 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 22 - The History of AI</itunes:title>
    <title>Episode 22 - The History of AI</title>
    <itunes:summary><![CDATA[In Episode 22 of '100 Days of Data,' Jonas and Amy trace the rich history of artificial intelligence—from Alan Turing's foundational question to today’s powerful transformers. They explore key eras including the rise and fall of symbolic AI, the breakthrough of neural networks, and the emergence of deep learning fueled by big data and GPU computing. Major milestones like IBM’s Deep Blue and Watson are discussed, showing how AI evolved from logical rules to language-based insights. The episode...]]></itunes:summary>
    <description><![CDATA[In Episode 22 of &apos;100 Days of Data,&apos; Jonas and Amy trace the rich history of artificial intelligence—from Alan Turing&apos;s foundational question to today’s powerful transformers. They explore key eras including the rise and fall of symbolic AI, the breakthrough of neural networks, and the emergence of deep learning fueled by big data and GPU computing. Major milestones like IBM’s Deep Blue and Watson are discussed, showing how AI evolved from logical rules to language-based insights. The episode highlights how different AI approaches have shaped industries like finance, healthcare, and retail, and underscores the importance of historical context in understanding the strengths and limitations of modern AI. By charting this journey, Jonas and Amy provide a grounded perspective for business leaders and tech professionals aiming to apply AI meaningfully today.]]></description>
    <content:encoded><![CDATA[In Episode 22 of &apos;100 Days of Data,&apos; Jonas and Amy trace the rich history of artificial intelligence—from Alan Turing&apos;s foundational question to today’s powerful transformers. They explore key eras including the rise and fall of symbolic AI, the breakthrough of neural networks, and the emergence of deep learning fueled by big data and GPU computing. Major milestones like IBM’s Deep Blue and Watson are discussed, showing how AI evolved from logical rules to language-based insights. The episode highlights how different AI approaches have shaped industries like finance, healthcare, and retail, and underscores the importance of historical context in understanding the strengths and limitations of modern AI. By charting this journey, Jonas and Amy provide a grounded perspective for business leaders and tech professionals aiming to apply AI meaningfully today.]]></content:encoded>
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    <pubDate>Tue, 02 Dec 2025 09:00:03 +0200</pubDate>
    <itunes:duration>438</itunes:duration>
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    <itunes:title>Episode 21 - What is AI?</itunes:title>
    <title>Episode 21 - What is AI?</title>
    <itunes:summary><![CDATA[In Episode 21 of '100 Days of Data,' Jonas and Amy demystify the world of Artificial Intelligence by breaking down what AI really is—and what it’s not. From its roots in rule-based logic to today’s data-driven machine learning systems, the hosts explore how AI operates, how businesses use it, and why it’s often misunderstood. They clarify common myths, distinguish between Narrow and General AI, and emphasize the importance of data quality, transparency, and ethical considerations. Through rea...]]></itunes:summary>
    <description><![CDATA[In Episode 21 of &apos;100 Days of Data,&apos; Jonas and Amy demystify the world of Artificial Intelligence by breaking down what AI really is—and what it’s not. From its roots in rule-based logic to today’s data-driven machine learning systems, the hosts explore how AI operates, how businesses use it, and why it’s often misunderstood. They clarify common myths, distinguish between Narrow and General AI, and emphasize the importance of data quality, transparency, and ethical considerations. Through real-world examples, like predictive maintenance in manufacturing and retail recommendation systems, the episode paints a grounded picture of AI as a powerful but practical tool. The hosts stress that AI isn&apos;t magical—it’s math, models, and data working at scale to mimic certain human cognitive tasks.]]></description>
    <content:encoded><![CDATA[In Episode 21 of &apos;100 Days of Data,&apos; Jonas and Amy demystify the world of Artificial Intelligence by breaking down what AI really is—and what it’s not. From its roots in rule-based logic to today’s data-driven machine learning systems, the hosts explore how AI operates, how businesses use it, and why it’s often misunderstood. They clarify common myths, distinguish between Narrow and General AI, and emphasize the importance of data quality, transparency, and ethical considerations. Through real-world examples, like predictive maintenance in manufacturing and retail recommendation systems, the episode paints a grounded picture of AI as a powerful but practical tool. The hosts stress that AI isn&apos;t magical—it’s math, models, and data working at scale to mimic certain human cognitive tasks.]]></content:encoded>
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    <pubDate>Mon, 01 Dec 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 20 - Cloud &amp; Data Platforms</itunes:title>
    <title>Episode 20 - Cloud &amp; Data Platforms</title>
    <itunes:summary><![CDATA[In Episode 20 of '100 Days of Data,' Jonas and Amy explore how cloud data platforms like AWS, Azure, and GCP have made scalable analytics accessible to organizations of all sizes. They discuss how cloud infrastructure replaces costly on-premise systems, allowing businesses to store, process, and analyze massive datasets with ease. Through real-world examples—from retail dashboards to fraud detection in banking—they highlight the benefits of elasticity, integration, and cost efficiency. The ep...]]></itunes:summary>
    <description><![CDATA[In Episode 20 of &apos;100 Days of Data,&apos; Jonas and Amy explore how cloud data platforms like AWS, Azure, and GCP have made scalable analytics accessible to organizations of all sizes. They discuss how cloud infrastructure replaces costly on-premise systems, allowing businesses to store, process, and analyze massive datasets with ease. Through real-world examples—from retail dashboards to fraud detection in banking—they highlight the benefits of elasticity, integration, and cost efficiency. The episode also covers key considerations like data governance, multi-cloud strategies, and cost control best practices, showing how cloud platforms don&apos;t just support analytics—they unlock AI capabilities by serving as the backbone for data-driven innovation.]]></description>
    <content:encoded><![CDATA[In Episode 20 of &apos;100 Days of Data,&apos; Jonas and Amy explore how cloud data platforms like AWS, Azure, and GCP have made scalable analytics accessible to organizations of all sizes. They discuss how cloud infrastructure replaces costly on-premise systems, allowing businesses to store, process, and analyze massive datasets with ease. Through real-world examples—from retail dashboards to fraud detection in banking—they highlight the benefits of elasticity, integration, and cost efficiency. The episode also covers key considerations like data governance, multi-cloud strategies, and cost control best practices, showing how cloud platforms don&apos;t just support analytics—they unlock AI capabilities by serving as the backbone for data-driven innovation.]]></content:encoded>
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    <pubDate>Fri, 28 Nov 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 19 - Big Data</itunes:title>
    <title>Episode 19 - Big Data</title>
    <itunes:summary><![CDATA[In Episode 19 of '100 Days of Data,' Jonas and Amy explore the foundational concept of Big Data through the lens of the 5 V’s: volume, velocity, variety, veracity, and value. They discuss how these five elements revolutionized data analytics and AI across industries, illustrating each with practical, real-world examples from healthcare, retail, logistics, and finance. The hosts emphasize that more data alone isn't enough—organizations must focus on data quality, relevance, and strategic value...]]></itunes:summary>
    <description><![CDATA[In Episode 19 of &apos;100 Days of Data,&apos; Jonas and Amy explore the foundational concept of Big Data through the lens of the 5 V’s: volume, velocity, variety, veracity, and value. They discuss how these five elements revolutionized data analytics and AI across industries, illustrating each with practical, real-world examples from healthcare, retail, logistics, and finance. The hosts emphasize that more data alone isn&apos;t enough—organizations must focus on data quality, relevance, and strategic value. From social media sentiment analysis to real-time vehicle tracking and cloud-based scalability, this episode highlights how understanding the 5 V’s helps leaders and data practitioners build smarter systems and drive meaningful insights. Listeners will gain a clear framework for assessing and maximizing the potential of their data assets in business and technology.]]></description>
    <content:encoded><![CDATA[In Episode 19 of &apos;100 Days of Data,&apos; Jonas and Amy explore the foundational concept of Big Data through the lens of the 5 V’s: volume, velocity, variety, veracity, and value. They discuss how these five elements revolutionized data analytics and AI across industries, illustrating each with practical, real-world examples from healthcare, retail, logistics, and finance. The hosts emphasize that more data alone isn&apos;t enough—organizations must focus on data quality, relevance, and strategic value. From social media sentiment analysis to real-time vehicle tracking and cloud-based scalability, this episode highlights how understanding the 5 V’s helps leaders and data practitioners build smarter systems and drive meaningful insights. Listeners will gain a clear framework for assessing and maximizing the potential of their data assets in business and technology.]]></content:encoded>
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    <pubDate>Thu, 27 Nov 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 18 - Data Mining</itunes:title>
    <title>Episode 18 - Data Mining</title>
    <itunes:summary><![CDATA[In Episode 18 of '100 Days of Data,' Jonas and Amy uncover the fundamentals of data mining, exploring how organizations turn vast amounts of information into valuable insights. From uncovering popular product pairings with association rules to detecting fraud through anomaly detection, this episode breaks down key data mining techniques in an engaging and practical way. The duo explains how clustering reveals hidden customer segments, and why asking the right business questions is crucial bef...]]></itunes:summary>
    <description><![CDATA[In Episode 18 of &apos;100 Days of Data,&apos; Jonas and Amy uncover the fundamentals of data mining, exploring how organizations turn vast amounts of information into valuable insights. From uncovering popular product pairings with association rules to detecting fraud through anomaly detection, this episode breaks down key data mining techniques in an engaging and practical way. The duo explains how clustering reveals hidden customer segments, and why asking the right business questions is crucial before diving into data. Real-world examples—from retail to finance—bring these concepts to life, and the CRISP-DM framework offers a structured path for success. Whether you&apos;re new to analytics or leading data initiatives, this episode provides a clear view into how data mining powers smarter decisions across industries.]]></description>
    <content:encoded><![CDATA[In Episode 18 of &apos;100 Days of Data,&apos; Jonas and Amy uncover the fundamentals of data mining, exploring how organizations turn vast amounts of information into valuable insights. From uncovering popular product pairings with association rules to detecting fraud through anomaly detection, this episode breaks down key data mining techniques in an engaging and practical way. The duo explains how clustering reveals hidden customer segments, and why asking the right business questions is crucial before diving into data. Real-world examples—from retail to finance—bring these concepts to life, and the CRISP-DM framework offers a structured path for success. Whether you&apos;re new to analytics or leading data initiatives, this episode provides a clear view into how data mining powers smarter decisions across industries.]]></content:encoded>
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    <pubDate>Wed, 26 Nov 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 17 - Statistics for Data Analysis</itunes:title>
    <title>Episode 17 - Statistics for Data Analysis</title>
    <itunes:summary><![CDATA[In Episode 17 of '100 Days of Data,' Jonas and Amy dive into the essential statistical concepts that underpin effective data analysis. They explain key terms like distributions, averages, and variance in clear, relatable language, illustrating how these tools help businesses uncover trends, measure risk, and make informed decisions. From understanding customer behavior to improving manufacturing consistency and forecasting sales more accurately, the hosts show how statistical literacy is vita...]]></itunes:summary>
    <description><![CDATA[In Episode 17 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the essential statistical concepts that underpin effective data analysis. They explain key terms like distributions, averages, and variance in clear, relatable language, illustrating how these tools help businesses uncover trends, measure risk, and make informed decisions. From understanding customer behavior to improving manufacturing consistency and forecasting sales more accurately, the hosts show how statistical literacy is vital—even if you&apos;re not a statistician. Whether you&apos;re working in finance, retail, or AI, grasping these foundational ideas will empower you to interpret data more confidently and ask smarter questions. Jonas and Amy also touch on real-world cases where misunderstanding averages or assuming normal distribution led to poor business choices, underscoring how mastering these basics pays off across industries.]]></description>
    <content:encoded><![CDATA[In Episode 17 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the essential statistical concepts that underpin effective data analysis. They explain key terms like distributions, averages, and variance in clear, relatable language, illustrating how these tools help businesses uncover trends, measure risk, and make informed decisions. From understanding customer behavior to improving manufacturing consistency and forecasting sales more accurately, the hosts show how statistical literacy is vital—even if you&apos;re not a statistician. Whether you&apos;re working in finance, retail, or AI, grasping these foundational ideas will empower you to interpret data more confidently and ask smarter questions. Jonas and Amy also touch on real-world cases where misunderstanding averages or assuming normal distribution led to poor business choices, underscoring how mastering these basics pays off across industries.]]></content:encoded>
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    <pubDate>Tue, 25 Nov 2025 21:11:37 +0200</pubDate>
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    <itunes:title>Episode 16 - Data Visualization</itunes:title>
    <title>Episode 16 - Data Visualization</title>
    <itunes:summary><![CDATA[In Episode 16 of '100 Days of Data,' Jonas and Amy explore the transformative power of data visualization in analytics. From charts and dashboards to storytelling and interactive tools, they examine how visuals turn raw data into actionable insights. The duo discusses visual cognition, design best practices, and common chart types—breaking down when and why to use them. Real-world examples illustrate how effective visualizations enable faster decisions, reveal hidden patterns, and increase tr...]]></itunes:summary>
    <description><![CDATA[In Episode 16 of &apos;100 Days of Data,&apos; Jonas and Amy explore the transformative power of data visualization in analytics. From charts and dashboards to storytelling and interactive tools, they examine how visuals turn raw data into actionable insights. The duo discusses visual cognition, design best practices, and common chart types—breaking down when and why to use them. Real-world examples illustrate how effective visualizations enable faster decisions, reveal hidden patterns, and increase trust in AI systems. Whether you&apos;re designing dashboards for executives or unraveling complex model outputs, this episode highlights why visualization is not just a design choice—it&apos;s a communication superpower every data practitioner needs.]]></description>
    <content:encoded><![CDATA[In Episode 16 of &apos;100 Days of Data,&apos; Jonas and Amy explore the transformative power of data visualization in analytics. From charts and dashboards to storytelling and interactive tools, they examine how visuals turn raw data into actionable insights. The duo discusses visual cognition, design best practices, and common chart types—breaking down when and why to use them. Real-world examples illustrate how effective visualizations enable faster decisions, reveal hidden patterns, and increase trust in AI systems. Whether you&apos;re designing dashboards for executives or unraveling complex model outputs, this episode highlights why visualization is not just a design choice—it&apos;s a communication superpower every data practitioner needs.]]></content:encoded>
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    <pubDate>Mon, 24 Nov 2025 15:31:21 +0200</pubDate>
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    <itunes:title>Episode 15 - Exploratory Data Analysis</itunes:title>
    <title>Episode 15 - Exploratory Data Analysis</title>
    <itunes:summary><![CDATA[In Episode 15 of '100 Days of Data,' Jonas and Amy dive into the world of Exploratory Data Analysis (EDA), the essential first step in any data project. With a mix of real-world examples and practical tools, they explore how EDA helps uncover hidden patterns, anomalies, and trends in messy datasets. From visualizing engine failure spikes in the automotive industry to identifying unusual spending patterns in finance, the hosts demonstrate the power of combining statistics with storytelling. Th...]]></itunes:summary>
    <description><![CDATA[In Episode 15 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of Exploratory Data Analysis (EDA), the essential first step in any data project. With a mix of real-world examples and practical tools, they explore how EDA helps uncover hidden patterns, anomalies, and trends in messy datasets. From visualizing engine failure spikes in the automotive industry to identifying unusual spending patterns in finance, the hosts demonstrate the power of combining statistics with storytelling. They also discuss tools ranging from Excel and Python’s Pandas to no-code platforms like Tableau, making EDA accessible to both analysts and business users. Whether it’s missing values or subtle correlations, this episode emphasizes that knowing your data well is key to building trustworthy AI systems and driving strategic decisions.]]></description>
    <content:encoded><![CDATA[In Episode 15 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of Exploratory Data Analysis (EDA), the essential first step in any data project. With a mix of real-world examples and practical tools, they explore how EDA helps uncover hidden patterns, anomalies, and trends in messy datasets. From visualizing engine failure spikes in the automotive industry to identifying unusual spending patterns in finance, the hosts demonstrate the power of combining statistics with storytelling. They also discuss tools ranging from Excel and Python’s Pandas to no-code platforms like Tableau, making EDA accessible to both analysts and business users. Whether it’s missing values or subtle correlations, this episode emphasizes that knowing your data well is key to building trustworthy AI systems and driving strategic decisions.]]></content:encoded>
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    <pubDate>Fri, 21 Nov 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 14 - Prescriptive Analytics</itunes:title>
    <title>Episode 14 - Prescriptive Analytics</title>
    <itunes:summary><![CDATA[In Episode 14 of '100 Days of Data,' Jonas and Amy dive into the world of prescriptive analytics—the analytical approach that goes beyond prediction to recommend specific actions. They explore how optimization, simulation, and decision-making frameworks work together to guide complex business decisions across industries like healthcare, retail, automotive, and finance. From designing smarter supply chains to crafting personalized marketing plans, prescriptive analytics uses AI-powered recomme...]]></itunes:summary>
    <description><![CDATA[In Episode 14 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of prescriptive analytics—the analytical approach that goes beyond prediction to recommend specific actions. They explore how optimization, simulation, and decision-making frameworks work together to guide complex business decisions across industries like healthcare, retail, automotive, and finance. From designing smarter supply chains to crafting personalized marketing plans, prescriptive analytics uses AI-powered recommendations to tackle uncertainty and operational constraints. The hosts also discuss real-world challenges, like model complexity, data quality, and stakeholder adoption, offering insights on how businesses can embed these tools effectively. Whether you&apos;re a data professional or a curious learner, this episode uncovers how smart analytics can drive proactive, impactful decisions.]]></description>
    <content:encoded><![CDATA[In Episode 14 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of prescriptive analytics—the analytical approach that goes beyond prediction to recommend specific actions. They explore how optimization, simulation, and decision-making frameworks work together to guide complex business decisions across industries like healthcare, retail, automotive, and finance. From designing smarter supply chains to crafting personalized marketing plans, prescriptive analytics uses AI-powered recommendations to tackle uncertainty and operational constraints. The hosts also discuss real-world challenges, like model complexity, data quality, and stakeholder adoption, offering insights on how businesses can embed these tools effectively. Whether you&apos;re a data professional or a curious learner, this episode uncovers how smart analytics can drive proactive, impactful decisions.]]></content:encoded>
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    <pubDate>Thu, 20 Nov 2025 09:00:04 +0200</pubDate>
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    <itunes:title>Episode 13 - Predictive Analytics</itunes:title>
    <title>Episode 13 - Predictive Analytics</title>
    <itunes:summary><![CDATA[In Episode 13 of '100 Days of Data,' Jonas and Amy explore predictive analytics—the art and science of using data to forecast what might happen next. From sales projections to patient readmission risks, they walk through real-world examples of how forecasting, regression, and other prediction models help businesses make smarter decisions. They break down essential concepts, discuss limitations like uncertainty and model assumptions, and highlight how industries like finance, healthcare, and m...]]></itunes:summary>
    <description><![CDATA[In Episode 13 of &apos;100 Days of Data,&apos; Jonas and Amy explore predictive analytics—the art and science of using data to forecast what might happen next. From sales projections to patient readmission risks, they walk through real-world examples of how forecasting, regression, and other prediction models help businesses make smarter decisions. They break down essential concepts, discuss limitations like uncertainty and model assumptions, and highlight how industries like finance, healthcare, and manufacturing are leveraging these tools for everything from credit scoring to predictive maintenance. Whether you&apos;re new to analytics or looking to refine your understanding, this episode offers practical insights and foundational knowledge to help you see how data can inform the future.]]></description>
    <content:encoded><![CDATA[In Episode 13 of &apos;100 Days of Data,&apos; Jonas and Amy explore predictive analytics—the art and science of using data to forecast what might happen next. From sales projections to patient readmission risks, they walk through real-world examples of how forecasting, regression, and other prediction models help businesses make smarter decisions. They break down essential concepts, discuss limitations like uncertainty and model assumptions, and highlight how industries like finance, healthcare, and manufacturing are leveraging these tools for everything from credit scoring to predictive maintenance. Whether you&apos;re new to analytics or looking to refine your understanding, this episode offers practical insights and foundational knowledge to help you see how data can inform the future.]]></content:encoded>
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    <pubDate>Wed, 19 Nov 2025 09:00:04 +0200</pubDate>
    <itunes:duration>434</itunes:duration>
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  <item>
    <itunes:title>Episode 12 - Diagnostic Analytics</itunes:title>
    <title>Episode 12 - Diagnostic Analytics</title>
    <itunes:summary><![CDATA[In Episode 12 of '100 Days of Data,' Jonas and Amy dive into the world of diagnostic analytics — the step beyond simply knowing what happened to understanding why it happened. They explore how businesses use tools like root cause analysis, variance analysis, and data mining to uncover underlying drivers behind data shifts. Through real-world examples in finance, healthcare, manufacturing, and retail, the hosts explain how diagnostic analytics helps identify problems at their source, rather th...]]></itunes:summary>
    <description><![CDATA[In Episode 12 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of diagnostic analytics — the step beyond simply knowing what happened to understanding why it happened. They explore how businesses use tools like root cause analysis, variance analysis, and data mining to uncover underlying drivers behind data shifts. Through real-world examples in finance, healthcare, manufacturing, and retail, the hosts explain how diagnostic analytics helps identify problems at their source, rather than just treating symptoms. The episode also highlights the importance of context, data quality, and domain expertise in making accurate diagnoses. Listeners will gain an understanding of when and how to apply diagnostic techniques to make more insightful, effective decisions based on their data.]]></description>
    <content:encoded><![CDATA[In Episode 12 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of diagnostic analytics — the step beyond simply knowing what happened to understanding why it happened. They explore how businesses use tools like root cause analysis, variance analysis, and data mining to uncover underlying drivers behind data shifts. Through real-world examples in finance, healthcare, manufacturing, and retail, the hosts explain how diagnostic analytics helps identify problems at their source, rather than just treating symptoms. The episode also highlights the importance of context, data quality, and domain expertise in making accurate diagnoses. Listeners will gain an understanding of when and how to apply diagnostic techniques to make more insightful, effective decisions based on their data.]]></content:encoded>
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    <pubDate>Tue, 18 Nov 2025 09:00:04 +0200</pubDate>
    <itunes:duration>487</itunes:duration>
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  <item>
    <itunes:title>Episode 11 - Descriptive Analytics</itunes:title>
    <title>Episode 11 - Descriptive Analytics</title>
    <itunes:summary><![CDATA[In Episode 11 of '100 Days of Data,' Jonas and Amy explore descriptive analytics — the vital first step in understanding data. They walk through how summarizing past performance via dashboards, KPIs, and descriptive statistics provides clarity that empowers better business decisions. Through real-world stories in retail, healthcare, and finance, they illustrate how good data and well-designed visuals can turn confusion into insight. This episode also outlines the importance of clean, timely, ...]]></itunes:summary>
    <description><![CDATA[In Episode 11 of &apos;100 Days of Data,&apos; Jonas and Amy explore descriptive analytics — the vital first step in understanding data. They walk through how summarizing past performance via dashboards, KPIs, and descriptive statistics provides clarity that empowers better business decisions. Through real-world stories in retail, healthcare, and finance, they illustrate how good data and well-designed visuals can turn confusion into insight. This episode also outlines the importance of clean, timely, and structured data to make descriptive analytics truly effective. You’ll learn how descriptive analytics fits into the broader analytics spectrum and why it’s essential not to jump ahead to advanced models before mastering the fundamentals.]]></description>
    <content:encoded><![CDATA[In Episode 11 of &apos;100 Days of Data,&apos; Jonas and Amy explore descriptive analytics — the vital first step in understanding data. They walk through how summarizing past performance via dashboards, KPIs, and descriptive statistics provides clarity that empowers better business decisions. Through real-world stories in retail, healthcare, and finance, they illustrate how good data and well-designed visuals can turn confusion into insight. This episode also outlines the importance of clean, timely, and structured data to make descriptive analytics truly effective. You’ll learn how descriptive analytics fits into the broader analytics spectrum and why it’s essential not to jump ahead to advanced models before mastering the fundamentals.]]></content:encoded>
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    <pubDate>Mon, 17 Nov 2025 09:00:05 +0200</pubDate>
    <itunes:duration>533</itunes:duration>
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    <itunes:episode>11</itunes:episode>
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  <item>
    <itunes:title>Episode 10 - The Value of Data</itunes:title>
    <title>Episode 10 - The Value of Data</title>
    <itunes:summary><![CDATA[In Episode 10 of '100 Days of Data,' Jonas and Amy explore how raw data transforms into actionable insights that drive business value. They unpack the concept of the data value chain—from collection and processing to analysis and insight extraction—and discuss the various forms of data monetization, including direct sales, operational optimization, and creating competitive assets. Real-world examples from retail, healthcare, and manufacturing illustrate how companies can leverage data to impr...]]></itunes:summary>
    <description><![CDATA[In Episode 10 of &apos;100 Days of Data,&apos; Jonas and Amy explore how raw data transforms into actionable insights that drive business value. They unpack the concept of the data value chain—from collection and processing to analysis and insight extraction—and discuss the various forms of data monetization, including direct sales, operational optimization, and creating competitive assets. Real-world examples from retail, healthcare, and manufacturing illustrate how companies can leverage data to improve decisions, enhance customer experiences, and strengthen market position. The episode also highlights the importance of data quality, privacy, ethics, and strategic alignment with business goals. Whether you&apos;re just beginning your data journey or looking to refine your approach, this episode offers a foundational guide to making data work for you.]]></description>
    <content:encoded><![CDATA[In Episode 10 of &apos;100 Days of Data,&apos; Jonas and Amy explore how raw data transforms into actionable insights that drive business value. They unpack the concept of the data value chain—from collection and processing to analysis and insight extraction—and discuss the various forms of data monetization, including direct sales, operational optimization, and creating competitive assets. Real-world examples from retail, healthcare, and manufacturing illustrate how companies can leverage data to improve decisions, enhance customer experiences, and strengthen market position. The episode also highlights the importance of data quality, privacy, ethics, and strategic alignment with business goals. Whether you&apos;re just beginning your data journey or looking to refine your approach, this episode offers a foundational guide to making data work for you.]]></content:encoded>
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    <pubDate>Sat, 15 Nov 2025 10:46:29 +0200</pubDate>
    <itunes:duration>474</itunes:duration>
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  <item>
    <itunes:title>Episode 9 - Metadata</itunes:title>
    <title>Episode 9 - Metadata</title>
    <itunes:summary><![CDATA[In Episode 9 of '100 Days of Data,' hosts Jonas and Amy explore the transformative power of metadata—data about data—and why it’s essential for making information searchable, trustworthy, and actionable. Using practical analogies and real-world business examples, they explain how metadata provides context, governs access, enhances searchability, and supports collaboration across teams. From digital catalogs to schema design and data lineage, the episode dives into how metadata underpins syste...]]></itunes:summary>
    <description><![CDATA[In Episode 9 of &apos;100 Days of Data,&apos; hosts Jonas and Amy explore the transformative power of metadata—data about data—and why it’s essential for making information searchable, trustworthy, and actionable. Using practical analogies and real-world business examples, they explain how metadata provides context, governs access, enhances searchability, and supports collaboration across teams. From digital catalogs to schema design and data lineage, the episode dives into how metadata underpins systems that empower both AI algorithms and human decision-makers. This foundational topic is brought to life with insights into metadata automation, standardization practices, and its crucial role in data governance and compliance. Whether you&apos;re a data novice or a seasoned professional, this episode highlights why managing metadata is key to unlocking the full value of data assets.]]></description>
    <content:encoded><![CDATA[In Episode 9 of &apos;100 Days of Data,&apos; hosts Jonas and Amy explore the transformative power of metadata—data about data—and why it’s essential for making information searchable, trustworthy, and actionable. Using practical analogies and real-world business examples, they explain how metadata provides context, governs access, enhances searchability, and supports collaboration across teams. From digital catalogs to schema design and data lineage, the episode dives into how metadata underpins systems that empower both AI algorithms and human decision-makers. This foundational topic is brought to life with insights into metadata automation, standardization practices, and its crucial role in data governance and compliance. Whether you&apos;re a data novice or a seasoned professional, this episode highlights why managing metadata is key to unlocking the full value of data assets.]]></content:encoded>
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    <pubDate>Thu, 13 Nov 2025 09:00:08 +0200</pubDate>
    <itunes:duration>426</itunes:duration>
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  <item>
    <itunes:title>Episode 7 - Data Storage</itunes:title>
    <title>Episode 7 - Data Storage</title>
    <itunes:summary><![CDATA[In Episode 7 of '100 Days of Data,' Jonas and Amy explore the evolution of data storage — from floppy disks to modern data lakes — and how different storage methods shape AI capabilities. They explain foundational concepts like files, relational databases, data warehouses, and data lakes, using real-world examples from industries like healthcare and automotive. The episode also highlights the critical role of cloud storage and integrated platforms in making data more accessible, scalable, and...]]></itunes:summary>
    <description><![CDATA[In Episode 7 of &apos;100 Days of Data,&apos; Jonas and Amy explore the evolution of data storage — from floppy disks to modern data lakes — and how different storage methods shape AI capabilities. They explain foundational concepts like files, relational databases, data warehouses, and data lakes, using real-world examples from industries like healthcare and automotive. The episode also highlights the critical role of cloud storage and integrated platforms in making data more accessible, scalable, and ready for innovation. Listeners will gain a clearer understanding of how each storage type serves specific business needs, and why choosing the right approach is crucial for data-driven success.]]></description>
    <content:encoded><![CDATA[In Episode 7 of &apos;100 Days of Data,&apos; Jonas and Amy explore the evolution of data storage — from floppy disks to modern data lakes — and how different storage methods shape AI capabilities. They explain foundational concepts like files, relational databases, data warehouses, and data lakes, using real-world examples from industries like healthcare and automotive. The episode also highlights the critical role of cloud storage and integrated platforms in making data more accessible, scalable, and ready for innovation. Listeners will gain a clearer understanding of how each storage type serves specific business needs, and why choosing the right approach is crucial for data-driven success.]]></content:encoded>
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    <pubDate>Wed, 12 Nov 2025 09:00:03 +0200</pubDate>
    <itunes:duration>498</itunes:duration>
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    <itunes:title>Episode 6 - Data Collection Methods</itunes:title>
    <title>Episode 6 - Data Collection Methods</title>
    <itunes:summary><![CDATA[In Episode 6 of '100 Days of Data,' Jonas and Amy delve into the essential process of data collection—the starting point of any AI journey. They explore four major methods: surveys for gathering subjective insights; logs that capture automated digital interactions; sensors that provide real-time physical measurements; and web scraping, a technical way to extract online information. Through real-world examples and practical advice, the hosts highlight how different methods suit different goals...]]></itunes:summary>
    <description><![CDATA[In Episode 6 of &apos;100 Days of Data,&apos; Jonas and Amy delve into the essential process of data collection—the starting point of any AI journey. They explore four major methods: surveys for gathering subjective insights; logs that capture automated digital interactions; sensors that provide real-time physical measurements; and web scraping, a technical way to extract online information. Through real-world examples and practical advice, the hosts highlight how different methods suit different goals—and how combining multiple sources can lead to richer, more accurate data for AI models. They also stress the importance of data quality, privacy, and ethical practices in collection. Whether it’s understanding customer behavior or tracking machine performance, this episode lays the groundwork for smarter, more responsible AI development.]]></description>
    <content:encoded><![CDATA[In Episode 6 of &apos;100 Days of Data,&apos; Jonas and Amy delve into the essential process of data collection—the starting point of any AI journey. They explore four major methods: surveys for gathering subjective insights; logs that capture automated digital interactions; sensors that provide real-time physical measurements; and web scraping, a technical way to extract online information. Through real-world examples and practical advice, the hosts highlight how different methods suit different goals—and how combining multiple sources can lead to richer, more accurate data for AI models. They also stress the importance of data quality, privacy, and ethical practices in collection. Whether it’s understanding customer behavior or tracking machine performance, this episode lays the groundwork for smarter, more responsible AI development.]]></content:encoded>
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    <pubDate>Tue, 11 Nov 2025 09:00:08 +0200</pubDate>
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    <itunes:title>Episode 8 - Data Formats</itunes:title>
    <title>Episode 8 - Data Formats</title>
    <itunes:summary><![CDATA[In Episode 8 of '100 Days of Data,' Jonas and Amy dive into the world of data formats—those essential structures like TXT, CSV, XML, and JSON that shape how information is stored, shared, and understood in AI systems. They break down the strengths and tradeoffs of each format, from the simplicity of plain text to the hierarchical power of XML and the lightweight flexibility of JSON. The conversation also explores how binary formats like JPEG, MP4, and others serve non-textual data like images...]]></itunes:summary>
    <description><![CDATA[In Episode 8 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of data formats—those essential structures like TXT, CSV, XML, and JSON that shape how information is stored, shared, and understood in AI systems. They break down the strengths and tradeoffs of each format, from the simplicity of plain text to the hierarchical power of XML and the lightweight flexibility of JSON. The conversation also explores how binary formats like JPEG, MP4, and others serve non-textual data like images and video. Real-world examples from healthcare, retail, and automotive industries illustrate how choosing the right format impacts everything from data integration to AI model success. This episode is a must for understanding the invisible backbone of data pipelines.]]></description>
    <content:encoded><![CDATA[In Episode 8 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the world of data formats—those essential structures like TXT, CSV, XML, and JSON that shape how information is stored, shared, and understood in AI systems. They break down the strengths and tradeoffs of each format, from the simplicity of plain text to the hierarchical power of XML and the lightweight flexibility of JSON. The conversation also explores how binary formats like JPEG, MP4, and others serve non-textual data like images and video. Real-world examples from healthcare, retail, and automotive industries illustrate how choosing the right format impacts everything from data integration to AI model success. This episode is a must for understanding the invisible backbone of data pipelines.]]></content:encoded>
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    <pubDate>Mon, 10 Nov 2025 09:00:03 +0200</pubDate>
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    <itunes:title>Episode 5 - Data Quality</itunes:title>
    <title>Episode 5 - Data Quality</title>
    <itunes:summary><![CDATA[In Episode 5 of '100 Days of Data,' Jonas and Amy delve into why data quality is essential to any successful AI initiative. They explore the three foundational pillars of data quality — accuracy, completeness, and consistency — through relatable stories ranging from retail and healthcare to manufacturing and finance. The hosts illustrate how flaws in data can lead to costly mistakes, missed opportunities, or outright failures in AI systems. They also discuss how human oversight, outdated syst...]]></itunes:summary>
    <description><![CDATA[In Episode 5 of &apos;100 Days of Data,&apos; Jonas and Amy delve into why data quality is essential to any successful AI initiative. They explore the three foundational pillars of data quality — accuracy, completeness, and consistency — through relatable stories ranging from retail and healthcare to manufacturing and finance. The hosts illustrate how flaws in data can lead to costly mistakes, missed opportunities, or outright failures in AI systems. They also discuss how human oversight, outdated systems, and lack of accountability often contribute to poor data quality. Practical tips for improving data integrity include validation rules, data audits, and establishing a single source of truth. Whether you&apos;re a data scientist, business leader, or AI enthusiast, this episode will deepen your understanding of how clean, trustworthy data lays the groundwork for intelligent decision-making.]]></description>
    <content:encoded><![CDATA[In Episode 5 of &apos;100 Days of Data,&apos; Jonas and Amy delve into why data quality is essential to any successful AI initiative. They explore the three foundational pillars of data quality — accuracy, completeness, and consistency — through relatable stories ranging from retail and healthcare to manufacturing and finance. The hosts illustrate how flaws in data can lead to costly mistakes, missed opportunities, or outright failures in AI systems. They also discuss how human oversight, outdated systems, and lack of accountability often contribute to poor data quality. Practical tips for improving data integrity include validation rules, data audits, and establishing a single source of truth. Whether you&apos;re a data scientist, business leader, or AI enthusiast, this episode will deepen your understanding of how clean, trustworthy data lays the groundwork for intelligent decision-making.]]></content:encoded>
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    <pubDate>Fri, 07 Nov 2025 09:01:03 +0200</pubDate>
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    <itunes:title>Episode 4 - The History of Data</itunes:title>
    <title>Episode 4 - The History of Data</title>
    <itunes:summary><![CDATA[In Episode 4 of '100 Days of Data,' Jonas and Amy trace the remarkable evolution of data storage—from ancient clay tablets to modern cloud infrastructure. They explore how civilizations captured and shared information, the origins of formal data systems like relational databases, and the rise of big data and cloud computing. Along the way, they connect historical milestones with today’s business challenges, such as data accessibility, security, and governance. The episode emphasizes that unde...]]></itunes:summary>
    <description><![CDATA[In Episode 4 of &apos;100 Days of Data,&apos; Jonas and Amy trace the remarkable evolution of data storage—from ancient clay tablets to modern cloud infrastructure. They explore how civilizations captured and shared information, the origins of formal data systems like relational databases, and the rise of big data and cloud computing. Along the way, they connect historical milestones with today’s business challenges, such as data accessibility, security, and governance. The episode emphasizes that understanding data’s history provides valuable context for managing modern data assets responsibly and effectively. Whether you&apos;re digitizing old inventory logs or deploying real-time AI models, appreciating where data comes from can shape how you use it today.]]></description>
    <content:encoded><![CDATA[In Episode 4 of &apos;100 Days of Data,&apos; Jonas and Amy trace the remarkable evolution of data storage—from ancient clay tablets to modern cloud infrastructure. They explore how civilizations captured and shared information, the origins of formal data systems like relational databases, and the rise of big data and cloud computing. Along the way, they connect historical milestones with today’s business challenges, such as data accessibility, security, and governance. The episode emphasizes that understanding data’s history provides valuable context for managing modern data assets responsibly and effectively. Whether you&apos;re digitizing old inventory logs or deploying real-time AI models, appreciating where data comes from can shape how you use it today.]]></content:encoded>
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    <itunes:title>Episode 3 - Sources of Data</itunes:title>
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    <itunes:summary><![CDATA[In Episode 3 of '100 Days of Data,' Jonas and Amy dive into the origins of data, exploring how people, machines, and sensors form the core sources fueling modern AI systems. From human-generated clicks and voice commands to machine logs and real-time sensor readings in IoT devices, the hosts explain how each type contributes uniquely to data-driven decision-making across industries. Real-world examples—from connected cars and smart healthcare to online retail—showcase the power and challenges...]]></itunes:summary>
    <description><![CDATA[In Episode 3 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the origins of data, exploring how people, machines, and sensors form the core sources fueling modern AI systems. From human-generated clicks and voice commands to machine logs and real-time sensor readings in IoT devices, the hosts explain how each type contributes uniquely to data-driven decision-making across industries. Real-world examples—from connected cars and smart healthcare to online retail—showcase the power and challenges of sourcing trustworthy, high-volume data. The episode also emphasizes the importance of data quality, infrastructure, and understanding the broader digital ecosystem to make effective use of AI. Whether you&apos;re a data professional or just getting started, this episode lays a crucial foundation for building smarter systems by starting at the source.]]></description>
    <content:encoded><![CDATA[In Episode 3 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the origins of data, exploring how people, machines, and sensors form the core sources fueling modern AI systems. From human-generated clicks and voice commands to machine logs and real-time sensor readings in IoT devices, the hosts explain how each type contributes uniquely to data-driven decision-making across industries. Real-world examples—from connected cars and smart healthcare to online retail—showcase the power and challenges of sourcing trustworthy, high-volume data. The episode also emphasizes the importance of data quality, infrastructure, and understanding the broader digital ecosystem to make effective use of AI. Whether you&apos;re a data professional or just getting started, this episode lays a crucial foundation for building smarter systems by starting at the source.]]></content:encoded>
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    <pubDate>Wed, 05 Nov 2025 09:00:00 +0200</pubDate>
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    <itunes:title>Episode 2 - Types of Data</itunes:title>
    <title>Episode 2 - Types of Data</title>
    <itunes:summary><![CDATA[In Episode 2 of '100 Days of Data,' Jonas and Amy dive into the foundational concept that not all data is created equal. They explore the three primary types of data—structured, unstructured, and semi-structured—offering real-world examples and insights into how each impacts AI workflows. From neatly organized spreadsheets to messy sensor logs and flexible JSON files, understanding these categories is crucial for effective data management and successful AI outcomes. Listeners learn how data f...]]></itunes:summary>
    <description><![CDATA[In Episode 2 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the foundational concept that not all data is created equal. They explore the three primary types of data—structured, unstructured, and semi-structured—offering real-world examples and insights into how each impacts AI workflows. From neatly organized spreadsheets to messy sensor logs and flexible JSON files, understanding these categories is crucial for effective data management and successful AI outcomes. Listeners learn how data formats influence everything from storage and processing to the performance of models and tools. With practical stories from finance, healthcare, and retail, this episode demystifies complex data types and emphasizes the value of identifying them early in any AI project.]]></description>
    <content:encoded><![CDATA[In Episode 2 of &apos;100 Days of Data,&apos; Jonas and Amy dive into the foundational concept that not all data is created equal. They explore the three primary types of data—structured, unstructured, and semi-structured—offering real-world examples and insights into how each impacts AI workflows. From neatly organized spreadsheets to messy sensor logs and flexible JSON files, understanding these categories is crucial for effective data management and successful AI outcomes. Listeners learn how data formats influence everything from storage and processing to the performance of models and tools. With practical stories from finance, healthcare, and retail, this episode demystifies complex data types and emphasizes the value of identifying them early in any AI project.]]></content:encoded>
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    <pubDate>Tue, 04 Nov 2025 09:00:00 +0200</pubDate>
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    <itunes:title>Episode 1 - What is Data?</itunes:title>
    <title>Episode 1 - What is Data?</title>
    <itunes:summary><![CDATA[In this kickoff episode of '100 Days of Data,' hosts Jonas and Amy lay the groundwork for understanding data in the modern world, especially its role in AI and business decision-making. They explore the essential distinctions between data, information, and knowledge, emphasizing how raw facts become meaningful insights when properly processed. With real-world examples—ranging from automotive sensors to retail inventory—they illustrate both the potential and pitfalls of working with data. The ...]]></itunes:summary>
    <description><![CDATA[In this kickoff episode of &apos;100 Days of Data,&apos; hosts Jonas and Amy lay the groundwork for understanding data in the modern world, especially its role in AI and business decision-making. They explore the essential distinctions between data, information, and knowledge, emphasizing how raw facts become meaningful insights when properly processed. With real-world examples—ranging from automotive sensors to retail inventory—they illustrate both the potential and pitfalls of working with data. The hosts also touch on critical themes like data quality, governance, and ethics, stressing why accuracy and intent matter. This episode sets the stage for deeper discussions by clarifying what data truly is and why it serves as the foundation for intelligent systems and smart decisions.]]></description>
    <content:encoded><![CDATA[In this kickoff episode of &apos;100 Days of Data,&apos; hosts Jonas and Amy lay the groundwork for understanding data in the modern world, especially its role in AI and business decision-making. They explore the essential distinctions between data, information, and knowledge, emphasizing how raw facts become meaningful insights when properly processed. With real-world examples—ranging from automotive sensors to retail inventory—they illustrate both the potential and pitfalls of working with data. The hosts also touch on critical themes like data quality, governance, and ethics, stressing why accuracy and intent matter. This episode sets the stage for deeper discussions by clarifying what data truly is and why it serves as the foundation for intelligent systems and smart decisions.]]></content:encoded>
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    <pubDate>Mon, 03 Nov 2025 09:00:00 +0200</pubDate>
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