Agentic AI with LangChain and LangGraph

Overview

Looking to advance your career by building next-generation AI applications? In this project-based course, you’ll dive deep into building agentic AI systems that can reason, reflect, and improve over time.

Using LangGraph and LangChain, you’ll learn to design stateful agents capable of self-evaluation, conditional execution, and iterative refinement. Explore powerful agent architecture through ReAct Agents and bring them to life through real-world projects like context-aware question answering and intelligent data retrieval workflows.

You’ll also step into the world of multi-agent collaboration, developing systems where agents specialize, communicate, and validate each other’s work to solve complex tasks. Whether you’re building agents that write, debug, query, or fact-check, this hands-on course gives you the skills to develop reliable, adaptive AI systems that think before they act—and get better with time.

Syllabus

• Introduction to LangGraph
• Build Self-Improving Agents with LangGraph
• Multi-Agent Systems and Agentic RAG with LangGraph

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Taught by

Faranak Heidari, Rachael, Karan Goswami, Joseph Santarcangelo, and IBM Skills Network Team

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Subjects

Computer Science