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Updated: Sep 30, 2026

No. of Questions: 162 Questions & Answers with Testing Engine

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CT-AI Practice Q&A's

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ISTQB CT-AI Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • Test Environments for AI-Based Systems: This section is about factors that differentiate the test environments for AI-based
Topic 3
  • systems from those required for conventional systems.
Topic 4
  • Using AI for Testing: In this section, the exam topics cover categorizing the AI technologies used in software testing.
Topic 5
  • 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 6
  • Machine Learning ML: This section includes the classification and regression as part of supervised learning, explaining the factors involved in the selection of ML algorithms, and demonstrating underfitting and overfitting.
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
  • 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 9
  • 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 10
  • 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 11
  • 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.

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

ISTQB CT-AI Exam Overview:

Certification Vendor:ISTQB
Exam Name:ISTQB Certified Tester AI Testing (CT-AI) Exam
Exam Number:CT-AI
Exam Duration:60 minutes
Real Exam Qty:40
Exam Format:Multiple Choice
Related Certifications:ISTQB Certified Tester Foundation Level (CTFL)
Certificate Validity Period:Lifetime
Available Languages:English
Passing Score:65%
Recommended Training:ISTQB Accredited Training Providers
Exam Registration:ISTQB Official Website
Sample Questions:ISTQB CT-AI Sample Questions
Exam Way:Online and onsite proctored exam via accredited ISTQB examination providers
Pre Condition:Recommended prior knowledge of ISTQB Foundation Level (CTFL) and basic understanding of software testing concepts and machine learning fundamentals.
Official Syllabus URL:https://www.istqb.org

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Frequently Asked Questions

What's the difference of the three versions of CT-AI study material?

Online test engine can supports Windows / Mac / Android / iOS, etc., because it is the software based on WEB browser. You can use it on any electronic device and practice with self-paced.
Online Test Engine supports offline practice, while the precondition is that you should run it with the internet at the first time.
Self Test Engine is suitable for windows operating system, running on the Java environment, and can install on multiple computers.
PDF version: can be read under the Adobe reader, or many other free readers, including OpenOffice, Foxit Reader and Google Docs.

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