Master RAG (Retrieval Augmented Generation) in Python – A Complete Beginner's Guide by a LangChain Expert 📚
Discover how to build RAG systems from the ground up with this comprehensive Python tutorial, led by a seasoned LangChain engineer. Perfect for AI enthusiasts eager to learn and implement advanced retrieval-augmented generation techniques.

freeCodeCamp.org
1.1M views • Apr 17, 2024

About this video
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
💻 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
Video Information
Views
1.1M
Likes
20.3K
Duration
02:33:11
Published
Apr 17, 2024
User Reviews
4.8
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