This course is your complete, hands-on guide to building Generative AI applications using LangChain—the most popular framework for developing large language model (LLM)-powered systems. You’ll start from the basics—understanding LangChain’s architecture, components, and models—and progressively move toward building real-world, production-ready AI tools.

You’ll learn how to design effective prompts, structure and parse model outputs, and connect various LangChain modules such as chains, runnables, retrievers, and vector stores. The course covers advanced concepts like Retrieval Augmented Generation (RAG), document loading, and tool calling, enabling your AI systems to reason over data and interact with external sources.

Through guided projects, you’ll build practical applications like YouTube-powered RAG chatbots and end-to-end AI agents, giving you the skills to go from concept to deployment.

What you will learn:

• Fundamentals and architecture of LangChain
• Working with prompts, structured output, and output parsers
• Building and chaining LLM workflows
• Using document loaders, text splitters, retrievers, and vector stores
• Implementing Retrieval Augmented Generation (RAG)
• Building functional chatbots and AI tools
• Tool calling and agent creation with LangChain
• Developing and deploying end-to-end AI systems