Free course material
Make retrieval prove its value.
RAG Systems
A practical path from retrieval foundations to evaluated, production-ready RAG systems.
What this course is about
A practical path from understanding to application.
Learn how retrieval-augmented generation connects language models to useful, current, and governed knowledge. The course moves from local foundations through hybrid search, evaluation, adaptive retrieval, and production design so learners can understand not only how to build a RAG pipeline, but how to tell whether it is working.
Covered material
What learners will work through.
- RAG foundations, embeddings, chunking, and vector search
- Metadata filtering, hybrid retrieval, reranking, and query transformation
- Grounded generation, citations, context engineering, and source quality
- RAG evaluation across retrieval, context, generation, citation, and operations
- GraphRAG, multimodal retrieval, corrective RAG, adaptive RAG, and agentic RAG
- Production architecture, observability, latency, cost, governance, and security
Who it is for
Meet learners where they are.
Developers, data practitioners, architects, product teams, and technical leaders who want a grounded understanding of RAG and the decisions behind reliable knowledge applications.
Adapt this course
Bring the material to your organization.
We can adapt the level, examples, exercises, and pace for executives, non-technical groups, technical teams, or mixed audiences. Sessions combine theory with practical and coding work where it fits, led by educators who meet with your group.
Book a custom training conversationRelated One+i service
GenAI & agent development
Connect open learning with the strategy, delivery, and adoption support around it.