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LangGraph Framework

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LangGraph Framework

This course is part of Hands-on Agentic AI: Building Intelligent Agents Specialization

Instructor: Hurix Digital

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

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This course is part of the Hands-on Agentic AI: Building Intelligent Agents Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

LangGraph Framework is an intermediate-level course designed for developers and AI engineers who want to build production-ready, stateful AI systems that go beyond simple prompt-response interactions. In today's AI landscape, the most powerful applications aren't single agents working in isolation—they're coordinated systems that maintain context, make intelligent decisions, and collaborate to solve complex problems. This course teaches you to harness LangGraph's graph-based architecture to create AI workflows with persistent memory, conditional logic, and multi-agent coordination. Through hands-on labs, real-world case studies from companies like Klarna, CyberArk, and Replit, and practical projects, you'll learn to build systems that maintain context across interactions, handle failures gracefully, and coordinate multiple specialized agents to create emergent intelligence. Whether you're building customer service automation, research assistants, or complex business workflows, this course equips you with the skills to create AI systems that are not just intelligent, but reliable, maintainable, and production-ready.

Module details

In this introductory lesson, learners will explore the fundamental architecture of LangGraph and understand how it differs from traditional agent frameworks. They'll examine the core concepts of graph-based state management and learn why LangGraph provides superior control and reliability for AI applications compared to stateless approaches.

What's included

4 videos3 readings1 assignment

4 videosTotal 26 minutes

Introduction and Welcome4 minutes
The LangGraph Advantage: Beyond Traditional Agent Frameworks6 minutes
Core Architecture: Nodes, Edges, and State Management6 minutes
Getting Started: Your First LangGraph Implementation10 minutes

3 readingsTotal 21 minutes

Welcome to the Course: Course Overview3 minutes
Real-World LangGraph Implementations: Production Case Studies8 minutes
LangGraph Development Environment and Tools10 minutes

1 assignmentTotal 15 minutes

HOL: Building Your First LangGraph Workflow15 minutes

In this lesson, learners will master the practical implementation of LangGraph's state management system. They'll learn to design persistent workflows with memory, implement conditional logic for dynamic routing, and create robust error handling mechanisms. Through hands-on exercises, learners will build workflows that maintain context across complex multi-step processes and handle real-world edge cases effectively.

What's included

3 videos1 reading1 assignment

In this final lesson, learners will master the design and implementation of sophisticated multi-agent systems using LangGraph. They'll learn to coordinate autonomous AI agents through event-driven flows, implement inter-agent communication patterns, and create systems where specialized agents collaborate to solve complex problems. The lesson culminates with a comprehensive capstone project that demonstrates production-ready multi-agent coordination.