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Episode 18: Fine-Tuning LLMs. – Nitya Narasimhan discusses enhancing pre-trained language models for specific tasks. The episode explains fine-tuning, its benefits, implementation, and limitations.

Episode 17: AI Agents. Korey Stegared-Pace introduces AI agents, detailing four agent frameworks, their unique features, and when to use them in generative AI applications.

Episode 16: Open Source Models and Hugging Face. – Explores open-source large language models. Korey Stegared-Pace highlights the benefits over proprietary models, guides on finding and using them on platforms like Hugging Face or Azure AI Studio, and discusses fine-tuning.

Episode 15: Retrieval Augmented Generation (RAG) and Vector Databases. – Bethany Jepchumba explores "grounding" LLMs with Retrieval Augmented Generation. Learn about RAG, its benefits, creating and using vector databases, and integrating RAG into applications.

Episode 14: The Generative AI Application Lifecycle. – Pablo Lopes discusses the generative AI lifecycle for developing, deploying, monitoring, and improving AI apps. The session highlights the transition from ML Ops to LLM Ops, covering tools, metrics, and evaluation for AI.

Episode 13: Securing Your Generative AI. – Explores AI security, as Korey Stegared-Pace discusses common risks and shares best practices for protecting generative AI applications.

Episode 12: Designing UX for AI. Bethany Jepchumba explores UX design for AI apps, highlighting user trust, transparency, and the importance of understanding user needs for effective collaboration and feedback.

Episode 11: Integrating Applications with Function Calling. Korey Stegared-Pace introduces function calling in LLMs, covering its implementation in OpenAI and integration into apps to enhance AI capabilities.

Episode 10: Building Low-Code AI Apps. – Someleze Diko demonstrates using Microsoft Power Platform's low-code tools with generative AI. Learn to create AI-powered apps and workflows using features like Copilot and AI Builder, all with minimal coding.

Episode 9: Building Image Generation Applications. Chris Noring and Pablo Lopes guide you in creating an image-generation app using text-to-image models like DALL-E and Midjourney.

Episode 8: Building Search Apps. Dave Glover demonstrates creating semantic search apps with vector embeddings, designing a search tool for an education startup's video library to find relevant segments.

Episode 7: Building Chat Applications. – Jasmine Greenaway shows how to efficiently create AI chat apps, covering customization, fine-tuning, and monitoring.

Episode 6: Text Generation Apps. – Explores text generation with OpenAI, demonstrating how to build an app by adjusting prompt, temperature, and tokens.

episode 5: creating advanced prompts. chris noring explores advanced prompt-engineering to enhance AI responses, using real-world examples.

episode 4: Understanding Prompt Engineering Fundamentals. nitya narasimhan covers prompt engineering basics—crafting and refining prompts for better AI results.

episode 3: responsibly using generative AI. explores the importance of fair, non-harmful AI outputs and improving responsible AI usage.

2/ episode 2: Exploring and Comparing Different LLMs. carlotta castelluccio and pablo lopes dive into different large language models, their industry uses, and business potential.

Episode 1: Intro to Generative AI & LLMs. – Carlotta Castelluccio explores Generative AI and large language models, highlighting their impact on industries, especially education.

🚨 BREAKING: Microsoft released an 18-episode series called "Generative AI for Beginners". Perfect for beginners, developers, and AI enthusiasts building a foundation. Here's a summary:👇