This beginner-focused masterclass introduces LangChain v0.2 and teaches how to build real-world AI applications using large language models like ChatGPT, Claude, and Gemini. It is designed for developers who want to understand how to build practical AI systems step by step with hands-on coding examples.

The course starts with environment setup and introduces chat models, showing how to create basic and real-time conversations with memory support. It then moves into prompt templates, explaining how to structure inputs effectively for better LLM responses.

You will also learn how chains work in LangChain, including sequential, parallel, and branching workflows. This helps in building structured AI pipelines instead of simple prompts.

A major part of the course is focused on Retrieval-Augmented Generation (RAG), where you learn how to build intelligent chatbots that use external data sources. Topics include text splitting, embeddings, retrievers, metadata handling, and conversational RAG systems.

The course also introduces agents and tools, showing how AI systems can decide actions and use external functions to solve tasks dynamically.

With over 20 real examples and full source code, this masterclass helps you move from beginner level to building functional AI applications using LangChain in real-world scenarios.