LangGraph Framework

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LangGraph Framework

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

Instructor: Hurix Digital

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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.

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Gain a foundational understanding of a subject or tool
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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.

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 videos Total 26 minutes

Introduction and Welcome 4 minutes
The LangGraph Advantage: Beyond Traditional Agent Frameworks 6 minutes
Core Architecture: Nodes, Edges, and State Management 6 minutes
Getting Started: Your First LangGraph Implementation 10 minutes

3 readings Total 21 minutes

Welcome to the Course: Course Overview 3 minutes
Real-World LangGraph Implementations: Production Case Studies 8 minutes
LangGraph Development Environment and Tools 10 minutes

1 assignment Total 15 minutes

HOL: Building Your First LangGraph Workflow 15 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

3 videos Total 23 minutes

Advanced State Management: Memory and Persistence 7 minutes
Conditional Logic and Dynamic Routing 7 minutes
Error Handling and Resilience Patterns 9 minutes

1 reading Total 8 minutes

Conditional Logic and Dynamic Workflows in Production 8 minutes

1 assignment Total 20 minutes

HOL: Implementing Robust State Management with Error Handling 20 minutes

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.

What's included

4 videos1 reading3 assignments

4 videos Total 31 minutes

Multi-Agent Architecture: Coordination and Communication 8 minutes
Design Patterns for Agent Collaboration 11 minutes
Advanced Multi-Agent Coordination Techniques 9 minutes
Congratulations and Continuous Learning Journey 3 minutes

1 reading Total 15 minutes

Multi-Agent Workflows in Enterprise Applications 15 minutes

3 assignments Total 80 minutes

HOL: Designing a Multi-Agent Research System 25 minutes
Project: Multi-Agent Workflow Implementation 45 minutes
Assessment 10 minutes

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Instructor

Hurix Digital

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371 Courses 30,271 learners

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