Advanced RAG is a hands-on course designed to help you build modern Retrieval-Augmented Generation systems from the ground up.

You will learn how production-grade RAG pipelines are designed, optimized, evaluated, and deployed using tools like LangChain, LangGraph, vector databases, and RAGAS.

Starting from RAG fundamentals, document processing, chunking, embeddings, and vector stores, the course gradually moves into advanced retrieval techniques such as Hybrid Search, MMR, Contextual Compression, Parent Document Retrieval, Multi-Query Retrieval, and Self-Query Retrieval.

You will also explore advanced RAG architectures including RAG Fusion, HyDE, Corrective RAG (CRAG), Self-RAG, and Graph RAG.

A major focus of the course is Agentic RAG with LangGraph, where you will learn how to build AI systems capable of reasoning, planning, reflection, and multi-step workflows.

The course also covers RAG evaluation using the RAGAS framework, along with production topics like caching, optimization, monitoring, debugging, security, and deployment.

By the end of the course, you will be able to build scalable and reliable RAG applications used in real-world AI products.

Course Duration: 40+ hours
Refund Policy: 4 days
Pre-Requisite & Curriculum: https://docs.google.com/document/d/1uZxKsZ4bV5PQL9qp6ifvVz_2UUjzIMW8Ny6pGDWRmh4/edit?usp=sharing