RAG Systems

Master the full RAG stack: chunking, embeddings, hybrid search, reranking, citations, evaluation, access control, and production deployment. Pulls from two courses — no need to take either in full if RAG is your target skill.

The route

1. RAG Systems (full phase) — ML & AI Engineering (phase 06). 9 lessons covering the complete RAG pipeline: decision framework, chunking, embeddings, vector stores, hybrid retrieval, reranking, query rewriting, citations, RAG evaluation, and access control.
2. Agentic RAG — Agentic AI Engineering (phase c2-03). 5 lessons on agentic RAG where the model decides what to retrieve — chunking strategies, hybrid search with cross-encoder reranking, RAGAS evaluation, and GraphRAG for multi-hop reasoning.

What you build

A production RAG system with hybrid search, reranking, citations, access control, and a RAGAS evaluation suite measuring faithfulness and precision.

Every learning path

Create a free account — the opening phases of 24 of 30 courses are free, no credit card. Or see Pro pricing.

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