Learn RAG

A structured learning path from RAG fundamentals to advanced architectures. Start with the basics and progressively build your understanding.

📍 Suggested Learning Path

1RAG Fundamentals→2Basic RAG→3Conversational→4Hybrid→5Agentic→6CRAG→7Self-RAG→8GraphRAG→9Multimodal

RAG Fundamentals

Beginner

What RAG is, why it matters, and how it works step by step. Start here.

~25 min read

Basic / Naive RAG

Beginner

The simplest RAG pipeline: load documents, chunk, embed, retrieve, and generate answers.

~30 min read

Conversational RAG

Intermediate

Add chat history and follow-up question resolution to RAG systems.

~25 min read

Hybrid RAG

Intermediate

Combine keyword search (BM25) with dense vector search for more accurate retrieval.

~30 min read

Agentic RAG

Advanced

Build AI agents that decide when and how to retrieve, using tools and conditional workflows.

~35 min read

Corrective RAG (CRAG)

Advanced

Evaluate retrieval quality and take corrective actions when results are insufficient.

~30 min read

Self-RAG

Advanced

Self-reflective retrieval and generation with answer quality evaluation.

~35 min read

GraphRAG

Advanced

Use knowledge graphs to capture entity relationships for relationship-aware retrieval.

~35 min read

Multimodal RAG

Advanced

Handle text, images, tables, and charts from mixed-media documents.

~30 min read