RAG in 60 Minutes
Build a question-answering system over your own documents. Upload, chunk, embed, search, and generate cited answers — the complete RAG pipeline.
"Ask questions about your company handbook and get cited answers"
6 Modules
Each module builds on the previous one. By the end, you have a complete production system.
- 1
What is RAG?
Understanding retrieval-augmented generation
- 2
Upload & Chunk
Document splitting with overlap
- 3
Embed & Store
Vector embeddings in pgvector
- 4
Search & Retrieve
Semantic search with relevance scoring
- 5
Generate Answers
LLM answers grounded in your docs
- 6
Add Citations
Source attribution and confidence scores
Production patterns you'll master
Synthetic data included
- Company handbook (PDF)
- FAQ documents (Markdown)
- Product docs (JSON)
- Policy updates (text)
- Meeting notes
What you walk away with
Shareable portfolio
A public URL showing your module timeline, patterns mastered, and completion status.
All the code
Download everything as a ZIP — pipelines, guardrails, deployment configs. Yours forever.
Module walkthrough
Each module documented with deliverables and the production pattern you implemented.
Ready to build your rag in 60 minutes?
First course free. $20 per course after that.