- Exam Code: CT-AI
- Exam Name: Certified Tester AI Testing Exam
- Updated: Oct 12, 2026
- Q & A: 162 Questions and Answers
ISTQB Certified Tester AI Testing : CT-AI exam
PDF Version DemoAbout ISTQB Certified Tester AI Testing : CT-AI Exam Questions
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ISTQB CT-AI Exam Syllabus Topics:
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Reference: https://www.istqb.org/certifications/artificial-inteligence-tester
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ISTQB Certified Tester AI Testing Sample Questions:
Question #1
Which of the following is an example of overfitting?
- A. The model discards data it considers to be noise or outliers
- B. The model is missing relationships between the inputs and outputs
- C. The model is not able to generalize to accommodate new types of data
- D. The model is too simplistic for the data
Correct Answer: C 🗳️
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Question #2
"AllerEgo" is a product that uses sell-learning to predict the behavior of a pilot under combat situation for a variety of terrains and enemy aircraft formations. Post training the model was exposed to the real- world data and the model was found to be behaving poorly. A lot of data quality tests had been performed on the data to bring it into a shape fit for training and testing.
Which ONE of the following options is least likely to describes the possible reason for the fall in the performance, especially when considering the self-learning nature of the Al system?
SELECT ONE OPTION
- A. The difficulty of defining criteria for improvement before the model can be accepted.
- B. The fast pace of change did not allow sufficient time for testing.
- C. There was an algorithmic bias in the Al system.
- D. The unknown nature and insufficient specification of the operating environment might have caused the poor performance.
Correct Answer: A 🗳️
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Question #3
An image classification system is being trained for classifying faces of humans. The distribution of the data is
70% ethnicity A and 30% for ethnicities B, C and D. Based ONLY on the above information, which of the following options BEST describes the situation of this image classification system?
SELECT ONE OPTION
- A. This is an example of expert system bias.
- B. This is an example of hyperparameter bias.
- C. This is an example of algorithmic bias.
- D. This is an example of sample bias.
Correct Answer: D 🗳️
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Question #4
The following confusion matrix represents the functional performance of a classifier.
Which ONE of the following is the correct calculation for the accuracy of the classifier?
- A. 3 60/ (60 + 9)' 100% = 87%
- B. 2 * (60 / (60 + 20) * 60 / (60 + 9)) / (60 / (60 + 20) + 60 / (60 + 9)) * 100% = 80%
- C. (60+ 11) / (60 + 11 + 20+ 9) * 100%-71%
- D. 60 / (60 * 20) * 100% = 75%
Correct Answer: C 🗳️
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Question #5
Which statement describes factors related to test data that make testing AI-based systems difficult?
Choose ONE option (1 out of 4)
- A. Using the same implementation for data acquisition by data scientists and testers prevents defect masking
- B. The input data must always be the same over time, especially in real-world systems
- C. Creating and managing large amounts of test data can be difficult, especially when it needs to be representative
- D. Artificially generated data requires legal approval and must be sanitized and encrypted
Correct Answer: C 🗳️
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