LangGraph Workflows (Beginner to Intermediate): Build Agentic AI Step-by-Step
Learn how to design, build, and debug LangGraph workflows for tool-using, stateful AI agents—from fundamentals to real multi-step examples.
Learn how to design, build, and debug LangGraph workflows for tool-using, stateful AI agents—from fundamentals to real multi-step examples.
LangGraph helps you build stateful, tool-using AI agent workflows that can handle complex, multi-step tasks. In this course, you will learn how to model agent logic as graphs, manage state properly, and build workflows that are easier to test and maintain.
Estimated completion time: 6–10 hours (self-paced). Includes labs and a capstone project.
You will build a complete agent workflow that uses tools, manages state, and produces structured outputs—ready to extend for real products.
Python basics (functions, modules, virtual environments)
Ability to run Python code locally
Basic understanding of LLMs is helpful (but not required)
Design and build LangGraph workflows confidently
Implement reliable tool-calling with correct argument passing
Manage and update workflow state properly
Debug multi-step agent flows with a structured approach
Build a reusable workflow template for future projects
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Students
0
Language
English
Duration
18h 00mLevel
intermediate
Expiry period
Lifetime
Certificate
yes
Dr. Kay
English
Certificate Course
0 Students
18h 00m
92 Courses
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