ISTQB CT-AI real exam prep : Certified Tester AI Testing Exam

Exam Code: CT-AI
Exam Name: Certified Tester AI Testing Exam
Updated: Jun 08, 2026
Q&As: 162 Questions and Answers

ISTQB CT-AI Value Pack (Frequently Bought Together)

PDF Version: Convenient, easy to study. Printable ISTQB CT-AI PDF Format. It is an electronic file format regardless of the operating system platform.

PC Test Engine: Install on multiple computers for self-paced, at-your-convenience training.

Online Test Engine: Supports Windows / Mac / Android / iOS, etc., because it is the software based on WEB browser.

Value Pack Total: $179.97 $79.99

About ISTQB CT-AI Real Exam

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ISTQB CT-AI Exam Syllabus Topics:

Topic	Details
Topic 1	systems from those required for conventional systems.
Topic 2	Methods and Techniques for the Testing of AI-Based Systems: In this section, the focus is on explaining how the testing of ML systems can help prevent adversarial attacks and data poisoning.
Topic 3	Testing AI-Based Systems Overview: In this section, focus is given to how system specifications for AI-based systems can create challenges in testing and explain automation bias and how this affects testing.
Topic 4	Introduction to AI: This exam section covers topics such as the AI effect and how it influences the definition of AI. It covers how to distinguish between narrow AI, general AI, and super AI; moreover, the topics covered include describing how standards apply to AI-based systems.
Topic 5	Using AI for Testing: In this section, the exam topics cover categorizing the AI technologies used in software testing.
Topic 6	ML Functional Performance Metrics: In this section, the topics covered include how to calculate the ML functional performance metrics from a given set of confusion matrices.
Topic 7	Quality Characteristics for AI-Based Systems: This section covers topics covered how to explain the importance of flexibility and adaptability as characteristics of AI-based systems and describes the vitality of managing evolution for AI-based systems. It also covers how to recall the characteristics that make it difficult to use AI-based systems in safety-related applications.
Topic 8	Neural Networks and Testing: This section of the exam covers defining the structure and function of a neural network including a DNN and the different coverage measures for neural networks.
Topic 9	Testing AI-Specific Quality Characteristics: In this section, the topics covered are about the challenges in testing created by the self-learning of AI-based systems.

Reference: https://www.istqb.org/certifications/artificial-inteligence-tester

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