Free iSQI CT-AI_v1.0_World Exam Questions
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iSQI CT-AI_v1.0_World Exam Questions
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Provided By: iSQI
- Exam: ISTQB Certified Tester AI Testing (v 1.0)
- Certification: ISTQB Certified Tester
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Total Questions: 296
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Updated On: Jun 06, 2025
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Rated: 4.9 |
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Online Users: 592
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Question 1
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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?
Answer: B
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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?
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Question 2
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There is a growing backlog of unresolved defects for your project. You know the developers have an ML
model that they have created which has learned which developers work on which type of software and the
speed with which they resolve issues. How could you use this model to help reduce the backlog and
implement more efficient defect resolution?
Answer: B
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There is a growing backlog of unresolved defects for your project. You know the developers have an ML
model that they have created which has learned which developers work on which type of software and the
speed with which they resolve issues. How could you use this model to help reduce the backlog and
implement more efficient defect resolution?
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Question 3
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Which of the following characteristics of AI-based systems make it more difficult to ensure they are safe?
Answer: C
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Which of the following characteristics of AI-based systems make it more difficult to ensure they are safe?
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Question 4
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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.
Answer: D
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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.
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Question 5
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A transportation company operates three types of delivery vehicles in its fleet. The vehicles operate at
different speeds (slow, medium, and fast). The transportation company is attempting to optimize scheduling
and has created an AI-based program to plan routes for its vehicles using records from the medium-speed
vehicle traveling to selected destinations. The test team uses this data in metamorphic testing to test the
accuracy of the estimated travel times created by the AI route planner with the actual routes and times.
Which of the following describes the next phase of metamorphic testing?
Answer: A
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A transportation company operates three types of delivery vehicles in its fleet. The vehicles operate at
different speeds (slow, medium, and fast). The transportation company is attempting to optimize scheduling
and has created an AI-based program to plan routes for its vehicles using records from the medium-speed
vehicle traveling to selected destinations. The test team uses this data in metamorphic testing to test the
accuracy of the estimated travel times created by the AI route planner with the actual routes and times.
Which of the following describes the next phase of metamorphic testing?