This course will guide you through the basics of Retrieval-Augmented Generation (RAG), starting with its fundamental concepts and components. You'll learn how to build a RAG system for chatting with documents, explore advanced techniques, and understand the pitfalls of naive RAG.
✏️ Course created by @vincibits
For the first fundamentals of the RAG part of the course, here's the GitHub link: https://github.com/pdichone/rag-intro-chat-with-docs
For the advanced RAG Techniques part of the course, here's the GitHub link: https://github.com/pdichone/advanced-rag-techniques
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⭐️ Contents ⭐️
⌨️ (
0:00:00) Intro
⌨️ (
0:02:22) RAG Fundamentals
⌨️ (
0:03:21) Components of RAG
⌨️ (
0:05:56) RAG Deep Dive
⌨️ (
0:07:56) Building a RAG System - Build an Application for Chatting with Our Documents
⌨️ (
0:32:52) Using Advanced RAG Techniques - Overview
⌨️ (
0:36:07) Naive RAG Overview and Its Pitfalls
⌨️ (
0:42:16) Naive RAG Drawbacks Breakdown
⌨️ (
0:48:28) Advanced RAG Techniques as the Solution - Query Expansion with Generated Answers
⌨️ (
0:54:23) Query Expansion with Generated Answers - Hands-on
⌨️ (
1:16:21) Query Expansion Summary
⌨️ (
1:17:44) Query Expansion with Multiple Queries - Overview
⌨️ (
1:20:57) Query Expansion with multiple Queries - Hands-on
⌨️ (
1:33:27) Your Turn - Challenge
⌨️ (
1:35:19) The End - Next Steps
🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
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👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama
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