Introduction to LangChain: Build AI Apps with Ollama

Ready to build custom AI applications on your own machine without relying on expensive APIs? This course demystifies large language models (LLMs) and shows you how to harness their power for practical projects using LangChain and Ollama. You will learn to set up a complete local development environment, connect to powerful open-source LLMs, and build functional applications from scratch. By the end, you'll be able to design and implement sophisticated RAG (Retrieval-Augmented Generation) systems to chat with your own documents and create foundational AI agents that can reason and take action. What you'll learn: - Understand the core concepts of LangChain, Ollama, and the architecture of LLM-powered applications. - Configure a local environment with Ollama to run popular open-source large language models. - Master modern prompt engineering and build flexible workflows with the LangChain Expression Language (LCEL). - Build a complete Retrieval-Augmented Generation (RAG) system to query and get answers from private documents. - Learn to reliably parse and structure LLM outputs into predictable formats like JSON for your applications. - Create simple AI agents that can use tools to perform tasks and make decisions. - Explore the fundamental principles of preparing your LangChain application for deployment. The course begins with foundational terminology and setup, then guides you through building progressively more complex applications, from simple chains to a fully functional RAG pipeline and basic agents. This course is designed for beginners. No prior experience with LangChain or AI development is required, though a basic understanding of Python will be helpful. Start reading and build your first AI application today.