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RAG

RAG Course

A hands-on series on building production-grade RAG systems. It covers the fundamentals of RAG, naive RAG, RAG evaluation, RAG optimization, Multimodal RAG, Graph RAG, Vision RAG, etc. (with implementation).

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Course content

  1. Foundations of RAG systems
  2. A Crash Course on Building RAG Systems – Part 2 (With Implementation)
  3. A Crash Course on Building RAG Systems – Part 3 (With Implementation)
  4. A Crash Course on Building RAG Systems – Part 4 (With Implementation)
  5. A Crash Course on Building RAG Systems – Part 5 (With Implementation)
  6. A Crash Course on Building RAG Systems – Part 6 (With Implementation)
  7. A Crash Course on Building RAG Systems – Part 7 (With Implementation)
  8. A Crash Course on Building RAG Systems – Part 8 (With Implementation)
  9. A Crash Course on Building RAG Systems – Part 9 (With Implementation)
  10. 16 Techniques to Supercharge and Build Real-world RAG Systems (Part 1)
  11. 16 Techniques to Supercharge and Build Real-world RAG Systems (Part 2)

RAG is a key NLP system that got massive attention due to one of the key challenges it solved around LLMs.

More specifically, if you know how to build a reliable RAG system, you can bypass the challenge and cost of fine-tuning LLMs.

That’s a considerable cost saving for enterprises.

And at the end of the day, all businesses care about impact. That’s it!

  • Can you reduce costs?
  • Drive revenue?
  • Can you scale ML models?
  • Predict trends before they happen?

Thus, the objective of this crash course is to help you implement reliable RAG systems, understand the underlying challenges, and develop expertise in building RAG apps on LLMs, which every industry cares about now.​

Of course, if you have never worked with LLMs, that’s okay. We cover everything in a practical and beginner-friendly way.

Updated on Jan 1, 2026