Artificial Intelligence is rapidly evolving from simple chatbots to autonomous AI agents capable of reasoning, using tools, maintaining memory, and solving complex tasks with minimal human intervention. As businesses increasingly adopt Agentic AI, skills in frameworks like LangChain and LangGraph have become highly valuable for developers and AI enthusiasts.
In this hands-on course, you’ll learn how to build intelligent AI agents from scratch using Python, LangChain, and LangGraph. We’ll start with the fundamentals of Agentic AI, exploring how large language models, prompts, memory, and tools work together to create autonomous systems. You’ll then build LLM-powered applications, add conversational memory, integrate external tools, and create custom Python tools for automation.
Next, you’ll move beyond traditional AI chains and discover how LangGraph enables powerful graph-based workflows. Through practical coding demonstrations, you’ll build autonomous agents using the ReAct architecture, implement state management and persistent memory, create human-in-the-loop approval workflows, and develop collaborative multi-agent systems with supervisor and worker agents.
