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

1. A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model.
Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?
SELECT ONE OPTION

A) Compare the R-Square score of the model obtained using two different implementations that utilize two different programming languages while using the same algorithm and the same training and testing data.
B) Add 10% of the rows randomly and create another model and compare the R-Square scores of both the model.
C) Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
D) Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.

2. Which ONE of the following approaches to labelling requires the least time and effort?
SELECT ONE OPTION

A) Outsourced
B) Internal
C) Al-Assisted
D) Pre-labeled dataset

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

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: