Develop AI Agents and Multi-Agent Systems for QA Practice using LangChain, LangGraph, and LLMs
Sub Category
- Other IT & Software
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Objectives
- Master Prompt Engineering techniques such as Chain-of-Thought reasoning, Role Assignment, and Few-Shot examples to design effective prompts for QA-AI Agents
- Build intelligent QA Agents using LangChain and LLMs that can automatically generate and refine BDD test cases from Jira user stories with human-in-the-loop
- Implement Retrieval-Augmented Generation (RAG) pipelines to enhance QA agents with contextual understanding using embeddings, chunking, and vector databases
- Develop and orchestrate Multi-Agent QA Systems using LangGraph, where a QA Manager agent delegates tasks between a qa_agent and qa_automation_agent
- Integrate AI-driven test automation by connecting LangChain tools with WebdriverIO to execute and validate end-to-end browser tests autonomously
Pre Requisites
- Basic understanding of software testing or QA processes is helpful but not mandatory
- Familiarity with Python programming (beginner level) will make it easier to follow along.
- Interest in AI, automation, or LLM-based systems will enhance your learning experience
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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