Free Lesson
Build RAG System with LangChain
60 min
Jan 25, 2026 9:00 PM
Virtual (Zoom)
In this video
What you'll learn
How Retrieval-Augmented Generation (RAG) Works
Understand the core concepts behind RAG and why it’s essential for building accurate, real-world AI applications.
How to Build RAG Pipelines Using LangChain
Learn how to combine documents, embeddings, vector stores, and LLMs into a working RAG system.
How to Use ChromaDB as a Vector Store for RAG
Integrate ChromaDB with LangChain to store embeddings and run semantic similarity search for RAG.
Why this topic matters
RAG is the most practical way for enterprises to extend LLM capabilities using proprietary data. LangChain provides the tools to build these systems efficiently, from document ingestion to secure retrieval and generation. This skill is now essential for building intelligent, scalable AI solutions for the enterprise.
You'll learn from
Nitin Monga
Tech Founder AI Agent Cafe
AI Engineer & Tech Founder AiAgentCafe
