Free ISTQB CT-AI Exam Questions

Become ISTQB Certified with updated CT-AI exam questions and correct answers

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Total 336 Questions | Updated On: Mar 21, 2026

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Question 1

An ML team asserts that the ML functional performance metrics based on validation data collected as part of training an ML model are sufficient for determining the quality of the system.

Which of the following statements is a valid reason to show that this may be INCORRECT?

A : lidation data is biased resulting in skewed functional performance measurements

B : ML functional performance metrics may not work well if the ground truth is not correct

C : ta may need to be transformed prior to training the model, so the functional performance measurements do not reflect the quality of the model

D : ML functional performance metrics cannot be used for measuring quality as these are tool dependent

Answer: B

Question 2

Consider a machine learning model where the model is attempting to predict if a patient is at risk for stroke. The model collects information on each patient regarding their blood pressure, red blood cell count, smoking, status, history of heart disease, cholesterol level, and demographics. Then, using a decision tree the model predicts whether or not the associated patient is likely to have a stroke in the near future. One the model is created using a training data set, it is used to predict a stroke in 80 additional patients. The table below shows a confusion matrix on whether or not the model mode a correct or incorrect prediction. The testers have calculated what they believe to be an appropriate functional performance metric for the model. They calculated a value of 2/3 or 0.6667.

A : F1 –source

B : Precision

C : Recall

D : Accuracy

Answer: D

Question 3

Which statement about using AI to analyze reported defects is MOST correct? Choose ONE option (1 out of 4)

A : ML models trained with critical defect tickets can identify defects that cause serious consequences.

B : ML models can support duplicate defect identification when checking defect criticality.

C : ML models can identify categories for a reported defect during assignment.

D : ML models identify developers who should handle a defect based on ticket content.

Answer: C

Question 4

Which of the following is an example of an input change where it would be expected that the AI system should be able to adapt?

A : It has been trained to recognize cats and is given an image of a dog.

B : It has been trained to recognize human faces at a particular resolution and it is given a human face image captured with a higher resolution.

C : It has been trained to analyze mathematical models and is given a set of landscape pictures to classify.

D : It has been trained to analyze customer buying trend data and is given information on supplier cost data.

Answer: B

Question 5

What is the correct definition of the term "artificial intelligence (AI)"?

A : measure of how well a classifier can distinguish between two classes

B : activity of identifying objects in images with bounding boxes to provide labelled data for classification

C : type of specialized hardware designed to accelerate AI applications

D : capability of an engineered system to acquire, process, create and apply knowledge and skills

Answer: D

Page: 1 / 68

Total 336 Questions | Updated On: Mar 21, 2026

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