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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

An image classification system is being trained for classifying faces of humans. The distribution of the data is
70% ethnicity A and 30% for ethnicities B, C and D. Based ONLY on the above information, which of the following options BEST describes the situation of this image classification system?
SELECT ONE OPTION

A. This is an example of expert system bias.
B. This is an example of hyperparameter bias.
C. This is an example of algorithmic bias.
D. This is an example of sample bias.

Question 2

Which ONE of the following options BEST DESCRIBES clustering?
SELECT ONE OPTION

A. Clustering requires you to know the classes.
B. Clustering is supervised learning.
C. Clustering is classification of a continuous quantity.
D. Clustering is done without prior knowledge of output classes.

Question 3

Arihant Meditation is a startup using Al to aid people in deeper and better meditation based on analysis of various factors such as time and duration of the meditation, pulse and blood pressure, EEG patters etc. among others. Their model accuracy and other functional performance parameters have not yet reached their desired level.
Which ONE of the following factors is NOT a factor affecting the ML functional performance?
SELECT ONE OPTION

A. The number of classes
B. The data pipeline
C. Biased data
D. The quality of the labeling

Question 4

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

Solutions: