ISTQB CT-AI Practice Exam: 30 Questions with Answers

Q: How similar are these practice questions to the real CT-AI exam?

These practice questions are designed to match the style, difficulty, and topic coverage of the real CT-AI exam. They follow the ISTQB question format with four options and one correct answer, cover all syllabus chapters proportionally, and test at appropriate cognitive levels (K1 remember, K2 understand, K3 apply). However, actual exam questions come from ISTQB question pools and may differ in specific wording or scenarios. Use these questions to identify knowledge gaps, not to memorize answers.

Q: What score should I aim for before taking the real exam?

Aim to consistently score 80% or higher on practice exams before scheduling the real test. The passing score is 65% (26/40 questions), but you want a comfortable margin. Scoring 80%+ consistently indicates you understand the material well enough to handle exam pressure and unexpected question variations. If you're scoring 65-75%, you might pass but should study more to be confident. Retake practice exams after studying weak areas.

Q: Which topics are most important for the CT-AI exam?

Based on syllabus structure, focus most on: Testing AI Systems (Chapters 7-8) covering test levels, automation bias, concept drift, and testing quality characteristics; Methods and Techniques (Chapter 9) including adversarial testing, metamorphic testing, and experience-based approaches; and Quality Characteristics (Chapter 2) covering explainability, fairness, bias, and robustness. ML Metrics (Chapter 5) is also important since questions often involve interpreting or calculating precision, recall, and F1 scores.

Q: How should I prepare for metric calculation questions?

Practice calculating precision, recall, and F1 from confusion matrices until it's automatic. Remember: Precision = TP/(TP+FP) answers 'Of positive predictions, how many were correct?' Recall = TP/(TP+FN) answers 'Of actual positives, how many did we catch?' F1 = 2*(Precision*Recall)/(Precision+Recall) balances both. Also understand when each metric matters: prioritize recall when false negatives are costly (cancer screening), precision when false positives are costly (spam filtering).

Q: How do I avoid common mistakes on the CT-AI exam?

Common mistakes include: confusing similar terms (explainability vs transparency, concept drift vs data drift), misreading negative questions (watch for NOT, EXCEPT, LEAST), forgetting AI-specific context (questions relate to AI testing, not general testing), and rushing through scenarios without identifying what's really being asked. Read questions twice, identify keywords, eliminate obviously wrong answers, and choose the BEST answer even when multiple seem partially correct.

Q: What if I fail the CT-AI exam?

If you don't pass, you can retake the exam without a mandatory waiting period. Review which topics you struggled with while the exam is fresh. Focus study on weak areas and take additional practice exams. Most candidates who fail pass on their second attempt after targeted preparation. The exam fee must be paid again, so thorough preparation before your first attempt is worthwhile.

Q: How long should I study before taking the CT-AI exam?

Study duration depends on your background. With strong AI/ML experience, 2-3 weeks part-time may suffice, focusing on testing-specific chapters. With strong testing background but limited AI exposure, budget 4-5 weeks to build AI foundations. With limited experience in both, plan 6-8 weeks. The key is consistent daily study (1-2 hours) rather than cramming. Take practice exams throughout to identify weak areas and track progress.

Q: Should I memorize the answers to these practice questions?

No, don't memorize answers. The real exam uses different questions, so memorization won't help. Instead, understand why each answer is correct and why others are wrong. Use practice questions to identify topics needing more study. If you get a question wrong, review the relevant syllabus section until you understand the concept. Practice questions are diagnostic tools for finding knowledge gaps, not answers to memorize.

Parul Dhingra13+ Years ExperienceHire Me

Senior Quality Analyst

Updated: 1/25/2026

This practice exam tests your knowledge across all chapters of the CT-AI syllabus. It contains 30 multiple-choice questions designed to simulate the real exam experience. The actual CT-AI exam has 40 questions, but this set provides comprehensive coverage of key topics.

Give yourself 45 minutes to complete this practice exam, simulating the time pressure of the real test.

Real exam details:

40 questions, 60 minutes
Passing score: 65% (26 out of 40)
Prerequisite: CTFL certification

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Exam Simulation: For the most realistic practice, complete all questions before checking answers. Time yourself and avoid looking up answers during the test.

Exam Instructions

Each question has one correct answer
No negative marking for wrong answers
Read each question carefully - look for keywords like "MOST," "BEST," "NOT," and "PRIMARY"
If unsure, eliminate obviously wrong answers to improve your chances
Mark difficult questions and return to them if time permits

Question Distribution

This practice exam covers all syllabus areas:

Topic Area	Questions
Introduction to AI	3
Quality Characteristics	4
Machine Learning	4
ML Data and Metrics	4
Testing AI Systems	5
Neural Networks	2
Methods and Techniques	4
Using AI for Testing	4
Total	30

Practice Exam Questions

Quiz on ISTQB CT-AI Practice Exam

Your Score: 0/30

Question: Which statement BEST describes the relationship between narrow AI and general AI (AGI)?

Both types exist today and are widely deployedNarrow AI performs specific tasks while AGI would possess human-level general intelligence; only narrow AI exists todayGeneral AI is simpler than narrow AINarrow AI requires more data than general AI

After the Exam

Scoring Your Results

Score Range	Assessment
27-30 (90%+)	Excellent - You're well prepared
23-26 (77-87%)	Good - Review weak areas
20-22 (67-73%)	Passing but close - More study recommended
Below 20 (< 67%)	More preparation needed

Next Steps Based on Your Score

If you scored 90% or higher:

You're likely ready to schedule your exam
Review the few questions you missed
Consider taking another practice exam to confirm readiness

If you scored 77-89%:

Review chapters where you made mistakes
Focus on understanding why answers are correct, not just which ones
Retake this practice exam in a few days

If you scored 67-76%:

Return to study materials for weaker areas
Review the CT-AI syllabus sections you struggled with
Practice calculating metrics from confusion matrices
Retake after more focused study

If you scored below 67%:

Work through each syllabus chapter systematically
Use our CT-AI Complete Guide
Review the official ISTQB syllabus
Don't schedule the real exam until you consistently score above 80%

Common Mistake Patterns

Confusing similar terms: Distinguish between explainability and transparency, concept drift and data drift, precision and recall, narrow AI and general AI.

Misreading negative questions: Watch for "NOT," "EXCEPT," and "LEAST" in questions.

Forgetting AI-specific context: Remember that CT-AI questions relate to AI testing, not general testing. Consider AI-specific concerns like non-determinism and the oracle problem.

Metric calculations: Practice calculating precision, recall, and F1 from confusion matrices until it's automatic.

Study Resources

Review these articles for topics you found challenging:

CT-AI Complete Guide - Comprehensive overview
Introduction to AI - AI fundamentals and quality characteristics
Quality Characteristics - Deep dive into AI quality
Machine Learning Overview - ML concepts and metrics
Testing AI Systems - Testing approaches for AI
Methods and Techniques - Adversarial, metamorphic, and other techniques
Using AI for Testing - AI tools for testing

Frequently Asked Questions

Frequently Asked Questions (FAQs) / People Also Ask (PAA)

How similar are these practice questions to the real CT-AI exam?

What score should I aim for before taking the real exam?

Which topics are most important for the CT-AI exam?

How should I prepare for metric calculation questions?

How do I avoid common mistakes on the CT-AI exam?

What if I fail the CT-AI exam?

How long should I study before taking the CT-AI exam?

Should I memorize the answers to these practice questions?

Using AI for Testing Complete Certification Guide