Learning track

Retrieval-Augmented Generation (RAG)

Learn Retrieval-Augmented Generation (RAG) from fundamentals to production-ready AI systems. This learning track covers retrieval architecture, embeddings, vector databases, chunking, indexing, search, reranking, generation, evaluation, observability, optimization, security, and production deployment.

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A structured path from foundations to production

Follow the lessons in order. The curriculum is managed in Payload and can grow without changing the public route structure.

Introduction to RAG
Start from the basics of Retrieval-Augmented Generation. Learn what RAG is, why it exists, what problems it solves, and how retrieval and large language models work together before building a RAG system.
1. Lesson 1
  What Is RAG? A Beginner's Introduction to Retrieval-Augmented Generation
  Learn what Retrieval-Augmented Generation (RAG) is, why it is needed, and how retrieval helps large language models answer questions using relevant external knowledge.