CuratedBeginner$20
RAG in 60 Minutes
Build a question-answering system over your own documents — upload, chunk, embed, search, and generate cited answers.
Modules
6
Verified
0
In Progress
0
What you walk away with
- ✓A shareable portfolio URL with your project walkthrough
- ✓Module-by-module timeline of everything you built
- ✓All the code — pipelines, guardrails, deployment configs
- ✓Production patterns documented on your profile
Claude CodeTypeScriptSupabasepgvector
Build your first RAG (Retrieval-Augmented Generation) pipeline from scratch. You'll understand why RAG beats fine-tuning for most use cases, split documents into searchable chunks, create vector embeddings and store them in pgvector, build semantic search with relevance scoring, generate grounded answers using retrieved context, and add source citations with confidence scores.