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

1. 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 neural network ML model with a current decision tree ML model for the same data.
C) 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
D) 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.

2. Which ONE of the following is the BEST option to optimize the regression test selection and prevent the regression suite from growing large?
SELECT ONE OPTION

A) Automating test scripts using Al-based test automation tools.
B) Using an Al-based tool to optimize the regression test suite by analyzing past test results
C) Identifying suitable tests by looking at the complexity of the test cases.
D) Using of a random subset of tests.

3. Which ONE of the following statements is a CORRECT adversarial example in the context of machine learning systems that are working on image classifiers.
SELECT ONE OPTION

A) These attacks can't be prevented by retraining the model with these examples augmented tothe training data.
B) These examples are model specific and are not likely to cause another model trained on same task to fail.
C) These attack examples cause a model to predict the correct class with slightly less accuracy even though they look like the original image.
D) Black box attacks based on adversarial examples create an exact duplicate model of the original.

4. Which ONE of the following tests is LEAST likely to be performed during the ML model testing phase?
SELECT ONE OPTION

A) Testing the speed of the prediction by the model.
B) Testing the speed of the training of the model.
C) Testing the accuracy of the classification model.
D) Testing the API of the service powered by the ML model.

Solutions: