RAG Handbook with Shivam Shrivastava

Want to learn RAG and build AI applications that can answer questions using your own documents?

This RAG Handbook is designed to help you understand Retrieval-Augmented Generation step by step, from basic concepts to advanced techniques and practical implementation.

What You Will Learn

• Introduction to RAG and how it works

• RAG vs Fine-Tuning

• Data preparation, document loading, and text chunking

• Embeddings and vector databases

• Retrieval methods, similarity search, and hybrid search

• Reranking and prompt engineering

• RAG architectures and evaluation metrics

• Context compression, Self-RAG, and Agentic RAG

• Graph RAG and Knowledge Graphs

• Corrective RAG (CRAG) and Multimodal RAG

• RAG with structured data, APIs, and external tools

• Building a complete RAG application using Python

• Real-world applications, testing, and troubleshooting

• Security, privacy, deployment, and production monitoring

• Interview questions, cheat sheets, and key terminology

Who Is This Handbook For?

• Beginners learning Generative AI and RAG

• Students preparing for AI and ML interviews

• Developers building AI-powered applications

• Data analysts and AI enthusiasts

• Professionals exploring LLMs, AI agents, and enterprise AI solutions

Why Get This Handbook?

Get structured learning material covering 50 topics, with easy-to-understand explanations, handwritten-style diagrams, flowcharts, code examples, and quick revision notes.

Price: ₹199

Start learning RAG and take your first step towards building practical AI applications.