Complete Agentic AI Bootcamp With LangGraph and Langchain

Are you excited about the future of AI where intelligent agents can think, act, and collaborate to solve complex tasks autonomously? Welcome to the **Complete Agentic AI Bootcamp with LangGraph and LangChain** — your one-stop course to master the art of building agentic AI applications from scratch! This course is designed to teach you everything you need to know about **Agentic AI, LangGraph, and LangChain** — two of the most powerful frameworks for building intelligent AI agents and multi-agent systems. You will start by understanding the fundamentals of *Agentic AI* — how it differs from traditional AI models, the key components of agents (memory, tools, decision-making), and real-world use cases. We will then dive deep into LangGraph, a cutting-edge framework that helps you design complex agent workflows using graphs, events, and state transitions. You’ll also learn how to combine LangChain's power with LangGraph to build production-ready agent applications. Throughout the course, you will build real-world projects step-by-step, including: - Creating single intelligent agents with memory and tool-usage capabilities. - Designing multi-agent collaboration systems with message passing and shared goals. - Implementing autonomous research assistants, task automation bots, and retrieval-augmented generation (RAG) agents. You will not just learn theory — you will build and deploy multiple end-to-end agentic applications, gaining real-world experience in constructing powerful AI systems. By the end of this course, you will have the skills and confidence to create your own *AI agents* and deploy complex agentic applications for various domains like search, research, task planning, customer support, and beyond.

What you'll learn:

• Understand the core principles of Agentic AI and how to design intelligent, autonomous agents for real-world tasks.
• Master building AI agents using LangGraph, including creating workflows, managing agent state, memory, and event-driven behavior.
• Develop and deploy multi-agent collaborative systems that can communicate, reason, and solve complex problems together.
• mplement hands-on projects to create powerful agentic applications like autonomous research agents, task automation systems, and knowledge retrieval assistants.