Eight modules. Every module ends with what to verify before you trust the output. Built by a QA engineer with ten years in the field, not an AI researcher.
Grounded in real standards and real tools
Standards references indicate alignment with publicly available syllabi. Terminology alignment, not accreditation or endorsement.
You can fail this exam. That's what makes passing it mean something. Finish all 8 modules, score 12 of 15 or better, and the certificate carries your name.
01 // THE APPROACH
Every module closes with a Check Yourself pass: the limitation to watch for, and what to confirm before you trust the output. Nothing here asks for blind faith in AI.
No ML background assumed. Prompts and workflows you can run in your job today, not research papers.
A real WCAG 2.1 AA audit and real automation frameworks back the claims, not toy demos built for slides.
It costs nothing, and it goes deeper than most of the QA AI courses people pay for.
02 // CURRICULUM
Why AI amplifies your testing instinct instead of replacing it, and the five-part anatomy of a prompt that actually works.
MODULE_02The five-component bug report structure, the actual prompt, severity classification, and the rubber-duck technique.
MODULE_03Generating a full test case draft in 15 minutes, pushing past the happy path, and realistic vs. adversarial test data.
MODULE_04The Persona Technique for reviewing your own coverage, and the BCU Framework for building a test strategy that doesn't fail.
MODULE_05The two manual accessibility checks that catch most real-world issues, no specialist tools required.
MODULE_06Prioritizing what to re-test, briefing AI on mobile-specific risk, and translating findings into language stakeholders act on.
MODULE_07The vibe coding workflow, Page Object Model, CI/CD, and what changes when you let AI generate the whole framework.
MODULE_08Why every AI chat starts from zero, and how a Claude Project or a CLAUDE.md file fixes it. Then: the 15-question certification.
03 // AUDIENCE
Manual testers who want AI in the daily workflow without needing a coding background first.
Vibe coding, Page Object Model, CI/CD, and where AI-generated frameworks actually fit.
What to standardize, what to verify, and how to brief a team on using AI responsibly.