ISTQB Certified Generative AI (CT-GenAI) Practice Exams

About this course

ISTQB Certified Tester – Testing with Generative AI (CT-GenAI) Practice Exam is designed to help software testers, QA professionals, test engineers, developers, test managers, and other technology professionals strengthen their understanding of how Generative Artificial Intelligence can be applied responsibly and effectively within software testing. As Generative AI becomes increasingly integrated into software development and quality engineering workflows, testing professionals need to understand not only how to use AI-based tools, but also how to evaluate their outputs, recognize their limitations, manage associated risks, and maintain appropriate human oversight.

This practice exam provides an opportunity to assess knowledge of important concepts associated with Generative AI and its application to testing activities. It can be used as a preparation resource for candidates studying toward the ISTQB Certified Tester – Testing with Generative AI (CT-GenAI) certification, as well as by professionals who want to evaluate their readiness before taking a formal examination.

This practice exam questions are intended to encourage understanding rather than simple memorization. Topics may include the fundamentals of Generative AI, large language models, AI-assisted test activities, prompt engineering, test case generation, test data generation, test automation support, defect analysis, test documentation, review of AI-generated content, risks associated with hallucinations and inaccurate outputs, security and privacy considerations, and the role of human judgment when incorporating Generative AI into testing processes.

A major focus of the practice exam is understanding that Generative AI can support testing professionals but does not eliminate the need for professional expertise. AI-generated test cases, scripts, requirements interpretations, defect descriptions, and other artifacts must be reviewed and validated before being relied upon. The quality of an AI-genera

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