{"id":3897,"date":"2026-06-10T16:06:10","date_gmt":"2026-06-10T14:06:10","guid":{"rendered":"https:\/\/ict-improve.nl\/training\/istqb-certified-tester-ai-testing-ct-ai-en\/istqb-certified-tester-ai-testing-ct-ai\/"},"modified":"2026-06-10T16:44:23","modified_gmt":"2026-06-10T14:44:23","slug":"istqb-certified-tester-ai-testing-ct-ai","status":"publish","type":"training","link":"https:\/\/ict-improve.nl\/en\/training\/istqb-certified-tester-ai-testing-ct-ai-en\/istqb-certified-tester-ai-testing-ct-ai\/","title":{"rendered":"ISTQB\u00ae Certified Tester AI Testing (CT-AI)"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"<p>Learning Objectives After completing this course you will be able to: Explain the fundamental concepts of Artificial Intelligence and Machine Learning. Differentiate between AI-based systems and conventional software systems. Identify AI-specific quality characteristics and quality risks. Understand machine learning workflows and model development processes. Interpret and apply ML functional performance metrics. Perform input data testing, including bias and representativeness testing. Select and apply appropriate testing techniques for AI-based systems. Test machine learning models throughout their lifecycle. Evaluate Generative AI systems and Large Language Models. Apply red teaming, adversarial testing and metamorphic testing techniques. Contribute to an effective test strategy for AI-based systems. Understand the impact of regulations and standards on AI testing. Prepare effectively for the ISTQB\u00ae Certified Tester AI Testing (CT-AI) examination. ISTQB\u00ae Certified Tester AI Testing (CT-AI) Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being applied in business-critical systems across many industries. While these technologies create significant opportunities, they also introduce new quality risks and testing challenges that cannot be addressed using traditional testing approaches alone. Data quality, bias, explainability, robustness, model drift, non-deterministic behaviour and Generative AI all require specialised testing knowledge and techniques. 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