ISTQB CT-AI 2.0 – 200 Practice Questions & Mock Exams
Prepare for the ISTQB Certified Tester AI Testing certification with 200 practice questions, 5 complete mock examinations, and detailed answer explanations.
Are you preparing for the ISTQB CT-AI 2.0 certification? Do you want to strengthen your knowledge of artificial intelligence, machine learning, and software testing techniques specifically designed for AI-based systems?
This comprehensive practice book is designed to help software testers, QA engineers, AI testing specialists, and IT professionals prepare for the ISTQB Certified Tester AI Testing examination.
Through realistic testing scenarios, structured mock examinations, and clear explanations, you can assess your understanding and develop the skills needed to evaluate AI-based software systems.
What's Inside This Book?
200 Original Practice Questions
Practice with 200 independently authored multiple-choice questions based on the ISTQB CT-AI 2.0 syllabus.
The questions cover theoretical concepts, practical AI testing scenarios, machine learning principles, and techniques for evaluating AI-based systems.
5 Full-Length Mock Examinations
Each mock examination includes:
40 practice questions
60-minute recommended time limit
44 available points
29/44 pass target
K2 and K3 cognitive-level questions
Questions covering all seven syllabus chapters
Practice under timed conditions and evaluate your progress as you prepare for certification.
Answer Keys and Detailed Explanations
Every mock examination includes an answer key and explanations to help you understand the reasoning behind the correct answers.
Review important distinctions, identify common mistakes, and strengthen your understanding of AI testing concepts.
Practical AI Testing Scenarios
Work through questions involving real-world challenges such as:
Evaluating AI model accuracy and performance
Testing machine learning datasets
Identifying bias and fairness concerns
Understanding data drift and concept drift
Evaluating AI robustness and reliability
Applying adversarial and metamorphic testing
Testing AI model integration and deployment
Calculating classification performance metrics
Learning Objectives and Progress Tracking
Use the learning-objective index, reusable answer sheet, exam blueprint, and score record to organize your preparation and identify areas requiring additional revision.
Topics Covered
1. Introduction to Artificial Intelligence
Understand the foundations of artificial intelligence, different AI approaches, AI-based architectures, and the challenges associated with intelligent systems.
2. Quality Characteristics for AI-Based Systems
Explore AI-specific quality characteristics, including robustness, fairness, safety, and other important considerations when evaluating AI systems.
3. Machine Learning
Develop your understanding of supervised and unsupervised learning, model training, data preparation, neural networks, and machine learning performance metrics.
4. Testing AI-Based Systems
Learn how traditional software testing principles can be adapted to AI-based systems, including test strategies, risk-based testing, and testing approaches for systems with non-deterministic behavior.
5. Input Data Testing
Explore data quality, representativeness, labeling, data preparation, and the importance of reliable datasets for machine learning.
6. Model Testing
Practice evaluating trained AI models using techniques such as adversarial testing, metamorphic testing, performance evaluation, and model comparison.
7. Machine Learning Development Testing
Understand testing considerations within machine learning development workflows, including validation of supporting tools and development processes.
Who Is This Book For?
Candidates preparing for ISTQB CT-AI 2.0 certification
Software testers and QA engineers
AI and machine learning testing specialists
Test automation engineers
Software developers working with AI-based applications
Quality assurance professionals transitioning into AI testing
IT professionals interested in testing machine learning systems
A Structured Approach to Exam Preparation
Each mock examination provides an opportunity to evaluate your knowledge through certification-style questions and practical scenarios.
Complete the examination under timed conditions, review the provided explanations, identify your knowledge gaps, and revisit the relevant syllabus topics.
The book helps you practice interpreting AI testing situations and selecting suitable testing techniques rather than simply memorizing definitions.
Publication Details
Author: Rafał Podraza
Edition: First Edition, October 2026
Language: English
Format: Digital PDF
Length: 75 pages
Total Questions: 200
Mock Examinations: 5
Syllabus Version: CT-AI 2.0
Important Information
This is an independently authored exam preparation book. It is not an official ISTQB publication and is not endorsed or accredited by ISTQB. The questions are original practice items, not confidential or recalled live examination questions. Certification results cannot be guaranteed.
Start practicing today and strengthen your knowledge of AI-based software testing!
