ModelRefs / Learn RAG — AI Learning Pathway
Learn RAG — AI Learning Pathway
Master Retrieval-Augmented Generation from indexing to evaluation. Design, build, and evaluate production-grade RAG systems. A 28-hour intermediate path.
Overview
Master Retrieval-Augmented Generation from indexing to evaluation.
What you will be able to do
- Architect a production RAG pipeline
- Choose embedding + vector store correctly
- Implement chunking, reranking, and evaluation
- Ship a RAG service with observability
Pathway phases
- Foundations — Embeddings, chunking, vector stores.
- Retrieval — Hybrid search and reranking.
- Production — Eval, observability, cost control.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Learn RAG — AI Learning Pathway.
Frequently asked questions
What will I learn in Learn RAG?
Architect a production RAG pipeline Choose embedding + vector store correctly Implement chunking, reranking, and evaluation
How long does Learn RAG take?
Approximately 28 hours across 3 phases.
What projects are included?
Internal Helpdesk RAG • RAG Evaluation Harness • Cited Answers Service • Cost-Aware Retrieval Router