Agentic AI with LangChain and LangGraph
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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
- Artificial Intelligence, Agentic AI Development, Python, LangChain & LangGraph Workflow Design, ReAct Agent Architecture, AI Agent
Offered By
- IBMSkillsNetwork
Estimated Effort
- 10 Hours
Platform
- Coursera
Last Update
- July 24, 2025
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
- 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
- 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
- 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

Language
- English
Topic
- Artificial Intelligence
Industries
- Information Technology
Skills You Will Learn
- Artificial Intelligence, Agentic AI Development, Python, LangChain & LangGraph Workflow Design, ReAct Agent Architecture, AI Agent
Offered By
- IBMSkillsNetwork
Estimated Effort
- 10 Hours
Platform
- Coursera
Last Update
- July 24, 2025
Instructors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreKunal Makwana
Data Scientist
I’m a passionate Data Scientist and AI enthusiast, currently working at IBM on innovative projects in Generative AI and machine learning. My journey began with a deep interest in mathematics and coding, which inspired me to explore how data can solve real-world problems. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and leveraging cloud technologies to extract meaningful insights from complex datasets.
Read moreKaran Goswami
Data Scientist
I am a dedicated Data Scientist and an AI enthusiast, currently working at IBM's Skills Builder Network. Learning how some simple mathematical operations could be used to make predictions and discover patterns sparked my curiosity, leading me to explore the exciting world of AI. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and extracting meaningful insights from complex datasets. I'm driven by a desire to apply these skills to solve real-world problems and make a meaningful impact through AI.
Read moreFaranak Heidari
Data Scientist at IBM
Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.
Read moreContributors
Hailey Quach
Data Scientist
Hi, I'm Hailey. I enjoy teaching others to build creative and impactful AI projects. By day, I’m a Data Scientist at IBM; by night, an Honors BSc student at Concordia University in Montreal, always exploring new ways to combine learning with innovation.
Read more