Agentic AI with LangChain and LangGraph

О курсе

Ready to build intelligent AI agents that can reason, improve, and collaborate? This hands-on course gives you the skills to build agentic AI systems using LangChain and LangGraph in just 3 weeks. You’ll design stateful workflows that support memory, iteration, and conditional logic. You’ll explore how to build self-improving agents using Reflection, Reflexion, and ReAct architectures, empowering your agents to reason about their outputs and refine them over time. Plus, you’ll work on guided labs where you’ll structure agent feedback, integrate external data, and generate context-aware responses through step-by-step reasoning. You’ll then develop collaborative multi-agent systems that coordinate tasks, retrieve relevant data, and solve complex problems using agentic RAG. Plus, you'll gain experience in agent orchestration, query routing, and governance strategies for building robust, scalable AI applications. By the end of the course, you’ll have built working prototypes of agentic systems and gained hands-on skills to design reliable, adaptable agents. Enroll today and get ready to power up your portfolio!

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Учитесь у экспертов

Faranak Heidari

Data Scientist/AI Developer

Kunal Makwana

GenAI Developer

Karan Goswami

Преподаватель курса

Joseph Santarcangelo

Ph.D., Data Scientist at IBM

Martin Keen

IBM Master Inventor - Academy of Technology - Technical Content Services