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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

Question 1

Which ONE of the following options describes the LEAST LIKELY usage of Al for detection of GUI changes due to changes in test objects?
SELECT ONE OPTION

A. Using a computer vision to compare the GUI before and after the test object changes.
B. Using a pixel comparison of the GUI before and after the change to check the differences.
C. Using a ML-based classifier to flag if changes in GUI are to be flagged for humans.
D. Using a vision-based detection of the GUI layout changes before and after test object changes.

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 bebehaving 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 unknown nature and insufficient specification of the operating environment might have caused the poor performance.
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 difficulty of defining criteria for improvement before the model can be accepted.

Question 3

A software component uses machine learning to recognize the digits from a scan of handwritten numbers. In the scenario above, which type of Machine Learning (ML) is this an example of?
SELECT ONE OPTION

A. Classification
B. Clustering
C. Regression
D. Reinforcement learning

Question 4

Which ONE of the following describes a situation of back-to-back testing the LEAST?
SELECT ONE OPTION

A. Comparison of the results of the current neural network ML model on the current data set with a slightly modified data set.
B. Comparison of the results of a current neural network model ML model implemented in platform A (for example Pytorch) with a similar neural network model ML model implemented in platform B (for example Tensorflow), for the same data.
C. Comparison of the results of a neural network ML model with a current decision tree ML model for the same data.
D. Comparison of the results of a home-grown neural network model ML model with results in a neural network model implemented in a standard implementation (for example Pytorch) for same data

Solutions: