Introduction-to-LLM-and-RAG

• Teacher: Xavier CORBIER
• Link: https://tinyurl.com/Xavier-LLM

Table of contents

• Session 1: Introduction to Large Language Models (LLMs)
  • Part 1: Overview of Language Models [Français]
  • Part 2: Introduction to Responsible AI [Français]
  • Part 3: Safety & Fairness Considerations for Generative Models [Français]
• Session 2: Working with Large Language Models
  • Part 1: Prompt Engineering [Français]
  • Part 2: Getting Started with ChatGPT [Français]
  • Part 3: The Top 10 ChatGPT alternatives to ChatGPT [Français]
• Session 3: Developing with Generative AI Models
  • Part 1: Getting Started with Hugging Face [Notebook Version]
  • Part 2: Fine tuning LLM [Notebook Version]
  • Part 3: What is Retrieval-augmented generation (RAG) [Français]
• Labs:
  • Exploring Prompt Engineering Techniques [Français]
  • Access a Free Generative AI API with Mistral AI and Groq [Français]
  • Building a Web Chat Application with a Generative AI [Français]
  • Building a Classification Pipeline Using a Generative AI [Français]
  • Setting Up a RAG (Retrieval-Augmented Generation) System for Technical Documentation [Français]

For further exploration

• Github: Your ultimate resource for LLM
• Datacamp: AI fundamentals
• Microsoft: Career path engineer AI

References

• Google: Getting started with Machine learning
• Stanford: Getting Started with ChatGPT
• Datacamp: The Top 10 ChatGPT Alternatives You Can Try Today
• FreeCodeCamp: How to Get Started with Hugging Face
• Datacamp: Fine tuning LLM
• Nvidia: What Is Retrieval-Augmented Generation, aka RAG?

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