Learn RAG From Scratch – Python AI Tutorial from a LangChain Engineer

Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer. This Python course teaches you how to use RAG to combine your own custom data with the power of Large Language Models (LLMs). 💻 Code: https://github.com/langchain-ai/rag-from-scratch If you're completely new to LangChain and want to learn about some fundamentals, check out our guide for beginners: https://www.freecodecamp.org/news/beginners-guide-to-langchain/ ✏️ Course created by Lance Martin, PhD. Lance on X: https://twitter.com/rlancemartin ❤️ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba) ⭐️ Course Contents ⭐️ ⌨️ (0:00:00) Overview ⌨️ (0:05:53) Indexing ⌨️ (0:10:40) Retrieval ⌨️ (0:15:52) Generation ⌨️ (0:22:14) Query Translation (Multi-Query) ⌨️ (0:28:20) Query Translation (RAG Fusion) ⌨️ (0:33:57) Query Translation (Decomposition) ⌨️ (0:40:31) Query Translation (Step Back) ⌨️ (0:47:24) Query Translation (HyDE) ⌨️ (0:52:07) Routing ⌨️ (0:59:08) Query Construction ⌨️ (1:05:05) Indexing (Multi Representation) ⌨️ (1:11:39) Indexing (RAPTOR) ⌨️ (1:19:19) Indexing (ColBERT) ⌨️ (1:26:32) CRAG ⌨️ (1:44:09) Adaptive RAG ⌨️ (2:12:02) The future of RAG 🎉 Thanks to our Champion and Sponsor supporters: 👾 davthecoder 👾 jedi-or-sith 👾 南宮千影 👾 Agustín Kussrow 👾 Nattira Maneerat 👾 Heather Wcislo 👾 Serhiy Kalinets 👾 Justin Hual 👾 Otis Morgan 👾 Oscar Rahnama -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news