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.



Agentic AI with LangChain and LangGraph
This course is part of multiple programs.



Instructors: Faranak Heidari
Access provided by Fractal
6,439 already enrolled
(37 reviews)
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What you'll learn
Build agentic AI systems using LangChain and LangGraph to support memory, iteration, and conditional logic
Design and implement self-improving agents using Reflection, Reflexion, and ReAct architectures
Apply agent orchestration techniques to build collaborative multi-agent systems
Implement agentic RAG systems that route queries and support retrieval-enhanced reasoning
Skills you'll gain
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11 assignments
July 2025
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There are 3 modules in this course
This module introduces LangGraph for building intelligent, stateful AI agents that support memory, iteration, and conditional logic. You’ll explore how nodes, edges, and shared state enable dynamic workflows, and how LangGraph extends LangChain for advanced control. Through foundational concepts and hands-on practice, you’ll learn to design, build, and execute workflows that reflect real-world agentic behavior
What's included
6 videos2 readings4 assignments1 app item5 plugins
This module focuses on building self-improving AI agents using LangGraph. You’ll explore and implement Reflection, Reflexion, and ReAct agent architectures to design workflows that evaluate and refine their own outputs. Through guided labs, you’ll gain hands-on experience creating agents that reason, integrate feedback, and improve performance using structured approaches grounded in reflection and prompt engineering.
What's included
5 videos1 reading4 assignments3 app items2 plugins
This module focuses on designing and implementing multi-agent systems using LangGraph. You’ll explore how specialized agents can collaborate to solve complex problems through structured orchestration. Key topics include core principles of multi-agent systems, collaboration patterns, and governance considerations. Through hands-on practice, you’ll build a multi-agent RAG system that dynamically routes queries to relevant data sources, gaining practical experience in coordinating specialized agents to enhance retrieval and reasoning.
What's included
4 videos3 readings3 assignments1 app item3 plugins
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Reviewed on Aug 21, 2025
Great overview and the insight into the coding aspects was invaluable!
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