Agentic Workflow Using LangChain and LangGraph
Compose agentic QA workflows in LangChain and LangGraph that plan, write and run tests.
- Duration
- 4 hours
- Lectures
- 26
- Level
- All Levels
- Learners
- Brand new
- Python
- LangChain
- LangGraph
- LLMs
- API testing
About this course
Compose true agentic workflows for QA — plans, cases, scripts, and live API testing, all in Python.
What you'll learn
- LangChain + LangGraph end-to-end
- Agents that write plans, cases, scripts
- API testing in the loop
What you'll build
A LangGraph orchestration for a QA workflow
Agents that produce test plans, test cases and scripts
API testing executed inside the graph
Human-in-the-loop approval steps
Project architecture
The pipeline you assemble across the course:
- Requirement
- Planner node
- Test case generator node
- Script generator node
- API test execution
- Review / approval node
- Final report
Curriculum overview
26 lectures · 4 hours of on-demand video.
01LangChain essentials
- Chains, tools and structured output
- Prompt design for QA tasks
02LangGraph orchestration
- Graph state and transitions
- Loops, retries and termination
03End-to-end QA workflow
- Plans → cases → scripts
- Executing API tests in the graph
FAQ
LangChain or LangGraph?
Both — LangChain for the building blocks, LangGraph for the stateful orchestration around them.
Is this advanced?
It is the deep end of the agentic track. Start with the AutoGen course if agents are new to you.
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Ready to start Agentic Workflow Using LangChain and LangGraph?
Lifetime access, 26 lectures, and a project you can put on your CV.