Your cart is empty.
Keep shoppingGenerative AI & AI Agents for QA: Complete SDET Masterclass
Hot & New
New
130 students
Generative AI & AI Agents for QA: Complete SDET Masterclass
Become an AI QA/SDET. Master Copilot, Claude Code, MCP, & n8n to build advanced multi-agent systems and QA agents.
Last updated 6/2026
English
What you'll learn
- Get a solid grasp of how Generative AI actually works and why it matters for software testing.
- Learn prompting techniques like Few-Shot and Chain-of-Thought that produce reliable, consistent test data.
- Build AI agents that can read a requirement doc and come out the other side with test scripts ready to run.
- Get hands-on with GitHub Copilot for fast scripting and Claude Code for terminal-based codebase refactoring.
- Use the Model Context Protocol to give LLMs secure, direct access to your code, databases, and test environments.
- Use n8n to visually wire together AI-powered pipelines that connect your agents with Jira.
- Build your own Claude tools so the AI plugs directly into your environment and acts within it.
- Walk away with a repeatable, production-ready approach to AI-augmented QA you can scale across any project.
Explore related topics
Course content
14 sections • 76 lectures • 10h 4m total length
Requirements
- No prior experience required to follow the course but good to have basic understanding of Software Testing and Test Automation
Description
QA is changing fast, and if you've been in the field for any amount of time, you've probably already felt it. The test scripts that used to be your bread and butter? They're not enough anymore. The engineers who thrive in the next few years won't just be the ones who know how to automate. They'll be the ones who know how to build systems that automate the automation.
That's exactly what this course is about.
This course isn't a "prompt ChatGPT to write your test cases" tutorial. It's a hands-on, ground-up guide to embedding Generative AI into the way you actually work, from the first requirement to the final bug report. You'll build production-grade test suites and set up AI agents that can read requirements, write code, chase down failures, and file bugs without you babysitting them.
Along the way, you'll get real experience with tools that are already reshaping the industry: GitHub Copilot for rapid scripting, Claude Code for refactoring entire codebases straight from your terminal, and n8n for wiring together AI-powered testing workflows that would've seemed like science fiction two years ago. You'll also go deep on the Model Context Protocol (MCP), one of the most exciting developments in AI right now, which lets you connect large language models directly to your testing tools and environments.
By the time you're done, you won't just be someone who uses AI to test software. You'll be someone who builds the agents doing the testing.
That's a very different career trajectory.
Who this course is for:
- Manual QA professionals who want to level up fast and land in roles where AI makes them more valuable, not replaceable.
- Automation Engineers and SDETs ready to move beyond scripts and start building AI workflows that run themselves.
- QA Leads and Managers who need a real, practical AI strategy for their team, not just a slide deck full of buzzwords.
- QA practitioners at any level who want to write prompts that actually work, consistently and predictably, not just by luck.