This course gives you a practical, end-to-end understanding of Agentic AI using LangGraph, the framework designed for building reliable, stateful, and controllable AI agents. You will learn what Agentic AI is, how it differs from Generative AI, and how LangGraph compares to tools like LangChain.

The course takes you through all the core LangGraph concepts—sequential, parallel, conditional, and iterative workflows—so you understand how agent behavior is structured and controlled. You will then build real projects such as chatbots, ChatGPT-style resume assistants, and LangGraph agents with persistence, streaming, and SQLite database integration.

You’ll also explore UI integrations using Streamlit, and learn to add observability with LangSmith, giving you production-grade monitoring and debugging capabilities. By the end, you will be able to design, build, deploy, and observe fully functional agentic systems powered by LangGraph.

What you will learn:

• Fundamentals of Agentic AI and how it differs from Generative AI
• LangGraph vs LangChain
• Core LangGraph concepts and workflow patterns
• Building chatbots and multi-step agent workflows
• Persistence, memory, and state management
• Streaming responses in LangGraph
• Integrating SQLite for data storage
• Building UI frontends with Streamlit
• Observability with LangSmith for debugging and monitoring
• Tools, integrations, and full agent pipelines in LangGraph