Episode 1: Introduction to Generative AI and LLMs – Carlotta Castelluccio introduces Generative AI and large language models, explaining their inner workings and how they are revolutionizing industries (with a focus on education)​ https://learn.microsoft.com/en...

Episode 2: Exploring and Comparing Different LLMs – Carlotta Castelluccio and Pablo Lopes explore various types of large language models, their use cases across industries, and how businesses can harness their potential​ https://learn.microsoft.com/en...

Episode 3: Using Generative AI Responsibly – Explains why responsible AI is crucial for generative applications, covering how to ensure AI outputs are fair and non-harmful, and steps to improve the responsible use of AI​ https://learn.microsoft.com/en...

Episode 4: Understanding Prompt Engineering Fundamentals – Nitya Narasimhan walks through the fundamentals of prompt engineering, teaching how to craft effective prompts and iterate on them to improve generative AI results​ https://learn.microsoft.com/en...

Episode 5: Creating Advanced Prompts – Chris Noring delves into advanced prompt-engineering techniques to optimize prompts and improve AI response quality, demonstrating these methods with real-world examples​ https://learn.microsoft.com/en...

Episode 6: Building Text Generation Applications – Covers the core concepts of text generation using OpenAI and shows how to build a text-generation application step by step, adjusting parameters like prompt, temperature, and tokens for desired output​ https://learn.microsoft.com/en...

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Episode 7: Building Chat Applications – Jasmine Greenaway demonstrates how to efficiently build and integrate AI-powered chat applications into existing systems, including customization, fine-tuning, and monitoring strategies​ https://learn.microsoft.com/en...

Episode 8: Building Search Apps (Vector Databases) – Dave Glover shows how to build semantic search apps using vector embeddings to index and query text, retrieving relevant video segments from an education startup's library. https://learn.microsoft.com/en...

Episode 9: Building Image Generation Applications – Chris Noring and Pablo Lopes explain how to generate images from text descriptions using models like DALL-E and Midjourney, and walk through building an image-generation app step by step​ https://learn.microsoft.com/en...

Episode 10: Building Low-Code AI Applications – Someleze Diko showcases Microsoft Power Platform's low-code tools with generative AI, featuring Copilot and AI Builder, to build AI-powered apps and workflows with little coding. https://learn.microsoft.com/en...

Episode 11: Integrating External Applications with Function Calling – Korey Stegared-Pace discusses function calling in LLMs, explains implementing an OpenAI function call, and shows integration into applications to enhance AI capabilities. https://learn.microsoft.com/en...

Episode 12: Designing UX for AI Applications – Bethany Jepchumba emphasizes designing AI app experiences by prioritizing user trust and transparency, understanding user needs, and fostering collaboration and feedback. https://learn.microsoft.com/en...

Episode 13: Securing Your Generative AI Applications – Discusses AI security, outlining risks and threats to generative AI and offering methods and best practices to secure these systems. https://learn.microsoft.com/en...

Episode 14: The Generative AI Application Lifecycle – Pablo Lopes examines the AI lifecycle, emphasizing the shift from ML Ops to LLM Ops with tools for developing, deploying, monitoring, and improving AI solutions. https://learn.microsoft.com/en...

Episode 15: Retrieval Augmented Generation (RAG) and Vector Databases – Bethany Jepchumba covers grounding LLMs with Retrieval Augmented Generation (RAG), explaining its basics, benefits, vector database setup, and app integration. https://learn.microsoft.com/en...

Episode 16: Open Source Models and Hugging Face – Explores open-source large language models. Korey Stegared-Pace contrasts these with proprietary versions and guides on using and fine-tuning open models on platforms on Hugging Face or Azure AI Studio. https://learn.microsoft.com/en...

Episode 17: AI Agents: LLMs using tools or frameworks for action. Korey Stegared - Pace defines AI agents, reviews four agent frameworks with unique features, and discusses using agent-based approaches in generative AI. https://learn.microsoft.com/en...

Episode 18: Fine-Tuning LLMs – Nitya Narasimhan explains fine-tuning pre-trained language models to enhance task-specific performance. This final episode covers what fine-tuning is, when it’s useful, how to do it, and its limitations. https://learn.microsoft.com/en...

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