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: Mar 28, 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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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?
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Question 4
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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
-
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?
-
Question 5
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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
-
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?