A practical foundation for QA work with AI: reviewing generated answers, testing AI features, and automation with Playwright/TypeScript, Selenide/Java, pytest/Playwright/Python, Cypress/TypeScript and WebdriverIO/TypeScript. Includes a shared local application, laboratory files, quizzes and a capstone.
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A practical foundation for QA work with AI: reviewing generated answers, testing AI features, and automation with Playwright/TypeScript, Selenide/Java, pytest/Playwright/Python, Cypress/TypeScript and WebdriverIO/TypeScript. Includes a shared local application, laboratory files, quizzes and a capstone.
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01Lektion 1AI in everyday QA work+
Theory and practice
ArtikelWhat to delegate to AI and who owns the result
ArtikelContext, prompting and answer review
WissenscheckCheck your understanding
02Lektion 2Testing an AI feature+
Theory and practice
ArtikelAn evaluation dataset and quality criteria
ArtikelPrompt injection and trust boundaries
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03Lektion 3Code foundations and the local laboratory+
Theory and practice
ArtikelFrom a manual scenario to code
ArtikelInstallation, Git and a reproducible run
WissenscheckCheck your understanding
04Lektion 4Playwright + TypeScript+
Theory and practice
ArtikelYour first test: locator, action, expectation
ArtikelDebugging, traces and AI code review
WissenscheckCheck your understanding
05Lektion 5Java + Selenide + JUnit+
Theory and practice
ArtikelHow Selenide, Selenium and JUnit fit together
ArtikelIsolation, waiting and maintaining Java tests
WissenscheckCheck your understanding
06Lektion 6Python + pytest + Playwright+
Theory and practice
ArtikelFixtures and parameterized checks
ArtikelData, diagnosis and refactoring Python tests
WissenscheckCheck your understanding
07Lektion 7Cypress + TypeScript+
Theory and practice
ArtikelThe command queue and observing a request
ArtikelStub or real request: what was tested
WissenscheckCheck your understanding
08Lektion 8WebdriverIO + TypeScript+
Theory and practice
ArtikelRunner, capabilities and asynchronous commands