ISTQB Artificial Intelligence Tester Sample Exams

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How will these sample exams help you in passing the Certified Artificial Intelligence exam?-My and my team at Nezam helped many students in passing different ISTQB certificates. We have wide experience that enabled us to create sample questions that cover the mostly important points in the syllabus. This will help you test your knowledge before applying for the real exam and be able to pass it from the first attempt.-What is special about these sample exams is that they are divided based on the chapters. So you can study the first 4 chapters and solve the first sample exam, then study chapters 5 to 7 and solve the second sample exam, then study chapter 8 to 11 and solve the third exam. Also there are two separate sample exams that test your knowledge about the ISTQB AI Tester glossary. They will help you in absorbing all concepts mentioned in the syllabus. Audience The Certified Tester AI Testing (CT-AI) qualification is aimed at people who are seeking to extend their understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI based systems and using AI to test. What are the entry criteria?To achieve the CT-AI certification, candidates must hold the ISTQB® Certified Tester Foundation Level (CTFL) certificate Business Outcomes Individuals who hold the ISTQB® Certified Tester- AI Testing certification should be able to accomplish the following business outcomes: Understand the current state and expected trends of AIExperience the implementation and testing of a ML model and recognize where testers can best influence its quality Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explainability Contribute to the test strategy for an AI-Based system Design and execute test cases for AI-based systems Recognize the special requirements for the test infrastructure to support the testing of AI-based systems Understand how AI can be used to support software testing