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0:00:00 - Course Overview
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Classroom Contents
Master RAG in N8N - Complete Beginner's Guide to Retrieval Augmented Generation
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- 1 0:00:00 - Course Overview
- 2 0:02:55 - SECTION 1 - What is RAG?
- 3 0:08:24 - 1.1 - Build Out Your First RAG Agent in N8N
- 4 0:13:32 - 1.2 - Setting up our Vector DB in Supabase
- 5 0:17:20 - 1.3 - Choosing an Embeddings Model
- 6 0:20:37 - 1.4 - Chunking Strategy
- 7 0:23:51 - 1.5 - Chunking Made Easy
- 8 0:27:23 - 1.6 - Load in Data
- 9 0:30:48 - 1.7 - Setting up Data Retrieval Agent RAG Agent
- 10 0:38:18 - SECTION 2 - Tackle Poor Quality Retrieval
- 11 0:45:33 - 2.1 - Poor Quality Retrieval & Contextual RAG
- 12 0:51:54 - 2.2 - Implementing Contextual RAG
- 13 0:59:30 - 2.3 - Dynamic file inputs
- 14 1:04:05 - 2.4 - Adding Context to our Chunks for Better Retrieval
- 15 1:07:13 - 2.5 - It’s difficult and slow to update!
- 16 1:15:11 - SECTION 3 - How to Update Data in a RAG database
- 17 1:17:58 - 3.1 - Handle new file formats
- 18 1:29:05 - 3.2 - Find and remove old records
- 19 1:37:23 - SECTION 4 - RAG Alternatives for Faster Retrieval
- 20 1:42:17 - 4.1 - CAG in N8N with OpenAI
- 21 1:49:28 - 4.2 - CAG in N8N using Anthropic
- 22 1:54:12 - Which is the best method?
