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RAG engineering course

Learn to build RAG systems that give grounded, cited answers

Retrieval-augmented generation (RAG) lets a language model answer from your documents. Module 8 teaches the whole pipeline, from parsing messy PDFs to measuring retrieval quality, on top of the Python, maths and LLM skills it needs.

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What you learn in Module 8 (RAG Engineering)

  • When to use RAG, and when not to. RAG vs fine-tuning vs a better prompt.
  • Parsing real documents. PDFs, tables and scanned pages, the step most tutorials skip.
  • Chunking strategies and their trade-offs (why fragmentation breaks answers).
  • Embeddings and vector databases (Chroma, Qdrant, pgvector).
  • Hybrid search, reranking, query rewriting and routing (hybrid search guide).
  • Grounded answers with citations, multilingual RAG for Indian languages, text-to-SQL and an introduction to graph-based retrieval.
  • Measuring retrieval with recall@k and MRR.

Module 8 has 13 lessons and about 30 guided hours. Module 9 (Evals, Guardrails & AI Security) then turns the RAG assistant into something you can trust in production, with an evaluation suite wired into CI.

Try the core idea now, free

Build a tiny semantic search in your browser in the free cosine similarity lab, or read RAG explained. Lesson 1.1 of the program is free too.

The modules behind RAG engineering

Every module unlocks in order, after the one before it.

Module 6LLM Application Engineering30 hours, 12 lessonsUnlocks after Module 5Module 8RAG Engineering30 hours, 13 lessonsUnlocks after Module 7Module 9Evals, Guardrails & AI Security24 hours, 11 lessonsUnlocks after Module 8

The program

13 modulesSelf-pacedOnline

The AI Engineering Program

From your first line of Python to production LLM apps, RAG, agents, evals and fine-tuning. Reverse-engineered from 2026 AI-engineer job descriptions.

13modules
346guided hours
12portfolio projects
6–14hours a week
PythonGitGitHubGoogle ColabJupyterpytestNumPypandasMatplotlib

₹56,999 ₹29,999

47% off 3rd anniversary offer

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Questions people ask

Still curious? Talk to us.

What is a RAG engineering course?

A course on building retrieval-augmented generation systems: getting documents into a searchable form, retrieving the right passages for a question and having a language model answer from them with citations, then measuring and improving retrieval quality.

Do I need to know machine learning first?

You need Python and the basics of LLM applications. The program teaches both before Module 8, in Modules 2 and 6, and modules unlock in order.

Which vector databases are used?

Module 8 covers embeddings and vector databases with Chroma, Qdrant and pgvector, plus hybrid search that combines keyword and vector retrieval.

Is there a RAG project?

Yes. Module 8 ends with a bilingual policy assistant: RAG over public Indian government documents in English and Hindi, with citations and a retrieval-quality report.

Your first lesson is on us.

AI vs ML vs DL vs GenAI: deep notes, a hands-on lab and a quiz. No card. No catch.

Start lesson 1 free