File Name: | Build GenAI & Multi-Agent Systems Tools for Software Testing |
Content Source: | https://www.udemy.com/course/genai-multi-agent-software-testing/ |
Genre / Category: | Other Tutorials |
File Size : | 3.8 GB |
Publisher: | Karthik KK |
Updated and Published: | July 5, 2025 |
Welcome to my course Build GenAI & Multi-Agent Systems Tools for Software Testing
In this hands-on course, you’ll learn to harness the power of Generative AI, AI Agents, and Multi-Agent Systems to build 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.
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
Who this course is for:
- QA
- Dev
- AI QA
- DevOps
- AI Agentic Engineers
DOWNLOAD LINK: Build GenAI & Multi-Agent Systems Tools for Software Testing
Build_GenAI_Multi-Agent_Systems_Tools_for_Software_Testing.part1.rar – 1000.0 MB
Build_GenAI_Multi-Agent_Systems_Tools_for_Software_Testing.part2.rar – 1000.0 MB
Build_GenAI_Multi-Agent_Systems_Tools_for_Software_Testing.part3.rar – 1000.0 MB
Build_GenAI_Multi-Agent_Systems_Tools_for_Software_Testing.part4.rar – 803.4 MB
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