RAG

Lesson in the Prompt Engineering Roadmap · Stage 2: Sampling Parameters

Last updated 14 September 2026

What is RAG?

Retrieval-Augmented Generation (RAG) combines LLMs with external knowledge retrieval to ground responses in verified, current information. RAG retrieves relevant documents before generating responses, reducing hallucinations and enabling access to information beyond the model's training cutoff. This approach improves accuracy and provides source attribution.

Study this in the interactive course See the whole Prompt Engineering roadmap

Free resources to learn RAG

Open sourceIntroduction to RAG - LlamaIndex
ArticleRetrieval Augmented Generation (RAG) - DAIR.AI

RAG: common questions

Can I learn RAG in Hindi?

This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain RAG in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.

Is this RAG tutorial for beginners?

It is lesson 20 of 46 in the free Prompt Engineering roadmap, in stage 2, Sampling Parameters. If you are new to Prompt Engineering, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.