Build GenAI & Multi-Agent Systems Tools for Software Testing

Build powerful AI Agents and Multi-Agent tools for QA workflows using LangChain and AutoGen — hands-on & practical !

What you'll learn
- Understand the power of LLMs in Software Testing
- Understand how to use LangChain to interact with LLMs
- Understand how to using Local LLMs with Ollama for Building Agent tools with LangChain
- Understand building AI Agents, MultiAgents and Toolings for Software Testing
- Understand the power of AI Agents to simplify Software Testing processes

Requirements
- Basic knowledge of python or any programming language
- Basic knowledge of working with ChatGPT or simple prompts

Description
Welcome to my courseBuild GenAI & Multi-Agent Systems Tools for Software Testing

In this hands-on course, you’ll learn to harness the power ofGenerative AI,AI Agents, andMulti-Agent Systemstobuild real-world tools for software testing. Whether you’re a QA engineer, SDET, or developer aiming to level up your automation skills, this course equips you with practical techniques to bring AI-driven efficiency into your testing lifecycle.

Today, QA engineers are no longer limited to writing test cases and checking logs manually. With the rapid growth ofLLMs (like ChatGPT, LLaMA, and Gemini)and frameworks likeLangChain and AutoGen, you can now buildautonomous test agents, automatelog analysis, and even createcollaborative multi-agent testing systems. This course gives you the tools, patterns, and hands-on skills to make that leap.

By the end of this course, you will be able to:

Understand the core concepts behind GenAI, AI Agents, and Multi-Agent Systems

Run powerful open-source LLMs locally using Ollama (no paid API needed)

Use LangChain to build intelligent tools and agents for QA automation

Create custom tools that read PDFs, parse logs, and generate test cases

Store and query data using vector stores with embeddings

Build a RAG-powered agent that analyzes logs using context retrieval

Develop a Test Case Generator Agent from product requirements

Use Playwright with agents to simulate web scraping and behavior testing

Orchestrate multi-agent collaboration using AutoGen and AutoGen Studio

Construct fully automated agents that read requirements and output test cases

Design multi-agent QA systems that mimic real QA workflows with minimal human input

Why This Course is Unique

Most AI courses focus on chatbots or language tasks. This course goesdeep into the testing lifecycleand shows you how tobuild intelligent, context-aware agentsfor software quality assurance. You’ll move beyond theory and actually build working tools that:

Read your requirements

Understand logs and test results

Generate test scripts and summaries

Work together as a team of AI testers

All usingopen-source tools,local models, andpractical Python code.

Who this course is for:
- QA
- Dev
- AI QA
- DevOps
- AI Agentic Engineers
More Info