- Course
LangGraph Essentials for Developers
Agentic AI workflows are transforming intelligent applications, and LangGraph is a leading framework to build them. This course will teach you how to code workflows, integrate tools, manage memory, use time travel, and trace executions.
Intermediate
- Course
LangGraph Essentials for Developers
Agentic AI workflows are transforming intelligent applications, and LangGraph is a leading framework to build them. This course will teach you how to code workflows, integrate tools, manage memory, use time travel, and trace executions.
Intermediate
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This course is included in the libraries shown below:
- AI
What you'll learn
Many developers can write simple LLM applications but find it challenging to implement complex, multi-step agentic workflows in code.
In this course, LangGraph Essentials for Developers, you’ll learn to build and code LangGraph workflows from scratch while mastering its key concepts.
First, you’ll explore the core components of a LangGraph workflow and learn to create sequential, conditional, parallel, and looping workflows, along with building a React agent.
Next, you’ll discover how memory is implemented, enabling features like human-in-the-loop and time travel.
Finally, you’ll learn how to implement streaming, build simple UIs with Streamlit, and trace your applications using LangSmith.
When you’re finished with this course, you’ll have the skills and knowledge of LangGraph needed to build, manage, and evaluate complete agentic AI workflows in code.
LangGraph Essentials for Developers
Intermediate
Table of contents
Deepali Srivastava is a Mathematics postgraduate, author, and passionate educator with over 15 years of experience teaching programming and Data structures. She has been involved in authoring books and creating educational content on programming, Data Structures & Algorithms and has reached more than 350,000 learners worldwide. Her books are used as reference materials by students and programmers. She is currently exploring Generative AI, focusing on LangChain and LangGraph frameworks to design intelligent agents, memory-powered workflows, and advanced RAG systems.
