You already know the RAG basics — retrieval, embeddings, chunking, generation. This course takes you into the territory that separates a working prototype from a production-grade, enterprise-ready RAG system.

Through 600 scenario-based practice questions across six comprehensive tests, you'll build the judgment to know not just what advanced RAG techniques exist, but when each one actually earns its complexity.

You'll cover:

Agentic & Self-Correcting RAG Patterns — ReAct, Self-RAG, Corrective RAG (CRAG), Reflexion, and adaptive retrieval strategies
Knowledge-Graph & Structured RAG — GraphRAG, RAPTOR, and RAG over structured, tabular, and SQL data
Multi-Modal & Multi-Source RAG — vision-language RAG, federated retrieval, temporal RAG, and audio/video content
Advanced Retrieval Architectures — RAG-Fusion, contextual retrieval, late chunking, speculative RAG, and multi-agent retrieval
Enterprise Security, Governance & Compliance — access control, PII handling, regulatory frameworks, auditability, and incident response
Advanced Scaling, Cost & Production Optimization — vector database scaling, inference cost optimization, capacity planning, and multi-region deployment

Every question comes with a full explanation, reinforcing a consistent theme throughout: sophisticated techniques are valuable exactly to the extent they solve real, evidenced problems — never simply because they're advanced. Whether you're architecting a new RAG system, hardening an existing one for production, or preparing for senior technical interviews in this space, this course gives you the systematic, evidence-based framework to make sound architectural decisions rather than chasing trends.