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Agentic AI with LangChain and LangGraph

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IntermediateCourse

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.

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Information Technology

Skills You Will Learn

  • Agentic AI Development, AI Agent, Artificial Intelligence, LangChain & LangGraph Workflow Design, Python, ReAct Agent Architecture

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 10 Hours

Platform

  • Coursera

Last Update

  • December 8, 2025
About this Course
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!

Learning Objectives: 

  • Build agentic AI systems using LangChain and LangGraph to support memory, iteration, and conditional control 
  • Design and implement self-improving agents using Reflection, Reflexion, and ReAct architectures 
  • Apply agent orchestration techniques to build collaborative multi-agent systems 
  • Develop agentic RAG systems that route queries and support retrieval-enhanced reasoning 

Course Syllabus

Module 1: Introduction to LangGraph 
  • Lesson 0: Welcome
  • Lesson 1: Introduction to Agentic AI 
  • Lesson 2: LangGraph versus LangChain
  • Lesson 3: Build a LangGraph Workflow
  • Lesson 4: Module Summary and Evaluation
Module 2: Build Self-Improving Agents with LangGraph
  • Lesson 1: Build Reflection Agents 
  • Lesson 2: Advanced Self-Improvement with Reflexion Agents 
  • Lesson 3: ReAct: Integrating Reasoning and Action
  • Lesson 4: Module Summary and Evaluation 
Module 3: Multi-Agent Systems and Agentic RAG with LangGraph 
  • Lesson 1: The Evolution from Single to Multiagent Systems
  • Lesson 2: Build Multi-Agent Applications
  • Lesson 3: Module Summary and Evaluation 
  • Lesson 4: Course Wrap-Up

Prerequisites

Python programming skills, basic understanding of LangChain, and familiarity with core AI concepts