Online course
6 modules, 2 months
Upskill
~20 hours of practice
Mastermind sessions
Final project
Stop spending half a sprint on repetitive paperwork
Test cases, checklists and test data — from requirements and user stories in minutes, plus a critical review of what the AI produced.
Online course6 modules, 2 monthsUpskill
AI for QA engineers
Hand your routine to AI: generate test cases, test data, SQL and bug reports in minutes, plug Copilot into your automated tests, and learn to test the AI features of the product itself.
Get a consultation
Illia Koval
QA Engineer at Esper Bionics, 5+ years of experience
Serhii Sakhnenko
Lead QA Engineer, 11+ years of experience
~20 hours of practiceMastermind sessionsFinal project~20 hours of practiceMastermind sessionsFinal project
In 2 months you will learn to:
Close bug reports, test reports and team updates in minutes
Bug reports, test plans, summaries and team updates — through AI, so formatting time goes back into the work itself.
Get the data yourself instead of waiting for a developer
SQL queries for data checks and API tests from Swagger — for your own task. No more waiting to get something out of the database.
Write automated tests without switching to AQA
With Copilot and Cursor you build basic Playwright tests and work out why CI/CD fails — without being an AQA.
Not be helpless when an LLM feature lands in your product
Hallucinations, non-determinism, evals, prompt injection, data leakage — and how to actually test all of it.
Come to your team lead with a map, not a hunch
You build an AI Use Map for your own project: where AI pays off and where it adds risk. And you defend it at the finish.
Detailed curriculum
6 modules, 17 topics — step by step
Learn from practitioners
Illia Koval
QA Engineer at Esper Bionics, 5+ years of experience
Tests bionic prostheses (software, hardware, firmware). Ex-QA at Uklon and Nova Pay with experience in high-load products.
Course author
Serhii Sakhnenko
Lead QA Engineer, 11+ years of experience
6 years as QA Lead at EPAM (teams of up to 24 people). Built testing from scratch to automation. Experienced in testing confidential LLM models.
Course author
Your AI-QA process starts here
Join to hand your routine to AI and become the person on the team who can test AI features.
6,000+
Mate academy graduates
80+%
of learning at Mate is practice
AI courses, courses about AI and an applied course for QA – what's the difference
When you look for AI courses, most offers on the market are general: how to use ChatGPT, write prompts, automate routine tasks. Courses of that format work if you are in any field and simply want to learn how to interact with neural networks.
AI tools for QA is a different story. It is not a course “about AI in general”, but an applied programme for testers: how to apply AI specifically in test design, automation and quality checks of AI products themselves. If you need not general AI courses but skills you can apply in a QA engineer's work right away, this is the direction.
QA (tester) courses: where AI fits in
Classic QA or tester courses teach the basics: test design, working with bug trackers, manual and automated testing. That is the foundation without which AI tools bring no results – AI amplifies skills, it does not replace them.
The logical path looks like this: QA or tester courses build the base first, and only then an applied AI course takes that base to the next level – systematising prompts, automation and testing of AI products.
AI specialist courses: how AI tools for QA boost a QA career
AI specialist courses are usually aimed at people who want to change direction completely and become an AI professional from scratch. But there is another way – stay a QA engineer and add AI as a tool inside your own profession.
That is exactly what the AI tools for QA course by Mate academy gives: 17 topics and 6 modules with practice, after which you can write reproducible prompts, review AI test cases for mistakes and test the AI product itself. It is not replacing a QA career with an AI specialisation, but levelling it up.