Course Description

Explore the innovative LangGraph framework and learn how to build AI agents modeled as graph-based systems. This course guides you through the fundamentals of LangGraph, teaching you to create agents that can manage complex data structures and tasks efficiently. Whether you're a beginner in AI or looking to enhance your skills, this course will equip you with the knowledge to design stateful applications and task-specific agents using LangGraph.

Course curriculum

  • 1
    Introduction to LangGraph
    • Course Introduction
    • Course Handouts (updated on 2024-12-18)
    • Introduction to LangGraph
    • LangGraph Components
    • States in LangGraph
    • Nodes Edges in LangGraph
    • Quiz
  • 2
    Hands-On: Build AI Agents with LangGraph
    • Hands On: Building Stateful Applications
    • Hands On: Building a Research Assistant in LangGraph
    • Hands On: Simple RAG Agent with LangGraph
    • Project: Creating a Conversational AI
    • Course Conclusion

Who Should Enroll

  • Aspiring Students: For those on their journey to mastering AI Agents, ready to explore different frameworks and make a mark in the tech world.

  • Professionals: Individuals looking to expand their skill set on AI agents and explore different frameworks of AI agents.

Key Takeaways

  • Basic understanding of the LangGraph framework.

  • In-depth Exploration of core components of LangGraph.

  • Hands-On Training with LangGraph.

About the Instructor

Lucas Soares - AI Engineer at Otovo | Specialist in LLM Applications & Computer Vision | Instructor at O'Reilly Media

Lucas Soares is an AI Engineer at Otovo, focusing on AI-driven solutions through large language models (LLMs) and computer vision. With 6+ years of experience across sectors like biometrics and retail, he excels in developing machine learning tools.
About the Instructor

FAQ

  • What is LangGraph?

    LangGraph is a framework that enables the creation of AI agents using graph-based models, allowing for complex data interactions and enhanced task management.

  • What are the key advantages of using LangGraph for AI agent development?

    LangGraph allows for highly flexible and scalable agent architectures, enabling complex data and task management through its graph-based approach, which is particularly effective for dynamic and stateful applications.

  • How does LangGraph compare to other AI frameworks?

    Unlike traditional linear or hierarchical AI frameworks, LangGraph utilizes a graph-based structure that offers more natural interaction patterns and can represent complex relationships and dependencies more effectively.

  • What types of applications can I develop with LangGraph?

    You can develop various applications, such as stateful AI agents for customer service, research assistants, data analysis tools, and more complex systems requiring nuanced decision-making.

  • Does this course include a certificate of completion?

    Yes, you will receive a certificate of completion upon successfully finishing the course and all associated assessments.