Learn AI Tools & Build AI Agents for Testing & QA Automation (Udemy.com)

It was very grateful and easy for me to learn this course "GenAI and AI Agents for QA Test Automation" which helped to increase my confidence for my career and also my future interviews. Thanks Rahul Shetty for your time and you made our learning comnfortable through your courses. Hoping to learn more courses in the future !!

This course is better suited for freshers than for experienced QA engineers or SDETs. While it touches on a wide variety of tools like Claude Code, n8n, MCP, and GitHub Copilot it ultimately feels like a 'jack of all trades, master of none.' A significant portion of the curriculum is dedicated to generic prompting and basic LLM usage, which feels far removed from actual, advanced QA-centric implementation. If you already have experience with agentic workflows or sophisticated test automation, you will likely find the vast majority of this content trivial. It is an introductory survey of current AI trends rather than the deep-dive engineering masterclass the title suggests.

Hey Rahul, you made testing so easy by teaching Agentic AI. Now its look like how simple, starting from creating scenarios, test cases, end to end automation, defect retesting (by providing JIRA ID) without manual intervention. I am in right place to learn about your automation and AI. I am very much happy. Thank you

Halfway through the *GenAI & AI Agents for QA Automation | Copilot & Claude Code* course, and it's been a great learning experience so far. The content is well-structured, easy to follow, and packed with practical examples that can be applied directly to real-world QA automation projects. The sections on AI-assisted testing, Copilot, and Claude Code are especially insightful. Looking forward to completing the remaining modules and implementing these concepts in my work.

Great knowledge and in depth as always. Some topics can go a bit too far in depth, which makes the course longer than needed. For some, this may be very helpful though. I have some great key takeaways from this course that I will be applying to my daily work.

The course content was excellent and provided a strong foundation in Generative AI, LLMs, MCP, Claude Code, and n8n with practical real-world examples that helped in understanding how these technologies work. The overview of AI-powered testing tools available in the market was also very informative and valuable. Thank you for creating such a useful and well-structured course.

"This is an incredible course! The instructor breaks down complex topics into bite-sized, easy-to-understand lessons. The real-world examples and hands-on projects were exactly what I needed to apply what I learned. I highly recommend this to anyone looking to master this subject!"

Comprehensive Fundamentals The course does an excellent job of covering AI testing terminology, privacy and security considerations, prompt engineering, token concepts, and context window limitations. These fundamentals provide a strong foundation for professionals entering AI-driven QA. Practical Application of AI in QA I appreciated how the course demonstrated using AI effectively for creating test plans, test cases, test strategies, and test data combinations directly from business requirements. This makes the learning highly practical and career-oriented. Hands-On Implementation with Copilot & MCP The real-world demos showing GitHub Copilot fixing code issues and speeding up automation development were very impactful. The deep dive into Model Context Protocol (MCP) and building automation agents across browsers, APIs, SQL, and workflows was a highlight. Agentic AI with Claude Code The section on building Agentic AI for Quality Engineering was outstanding. Learning how to design domain knowledge skills, avoid context bloat, and create agents that can generate, run, and fix tests added immense value. Business-Oriented Automation Flows The integration of AI agents with n8n workflows, Jira, and Google Sheets showcased how to build practical, business-ready automation solutions. This makes the course not just theoretical but directly applicable to enterprise QA environments.

This course was designed with a great mix of strong theoretical concepts and practical demos. As a manual tester transitioning into automation, I found these skills to be exactly what’s needed to stand out in the industry. I’d highly recommend this to anyone looking to level up their career in QA.

it would be great if you could uploaded all the course related docs and code base in github then it will be easy for the learners to access or download it anytime when they needed. Otherwise its really nice course, Appreciate it.