What you'll learn

LLMs are powerful, but without grounding, they can hallucinate. Retrieval-augmented generation (RAG) solves this by combining generation with contextual search. In this course, Deploying and Maintaining RAG Systems, you’ll learn to build scalable, accurate, and observable AI services that use retrieval as a first-class citizen. First, you’ll explore the architecture and core building blocks of a modern RAG system. Next, you’ll learn how to deploy and serve RAG systems in production with API endpoints, monitoring, and rollback strategies. Finally, you’ll optimize retrieval performance, compression, and cost-efficiency at scale. When you’re finished, you’ll have the skills to confidently operate a production-ready RAG service and make informed decisions around observability, latency, and scale.