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

1. Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems?
SELECT ONE OPTION

A) Nature of data constantly changes with lime.
B) Test data being sourced from public sources.
C) Compliance needs require proper care to be taken of input personal data.
D) Data for the use case is being generated at a fast pace.

2. Which ONE of the following options describes a scenario of A/B testing the LEAST?
SELECT ONE OPTION

A) A comparison of two different websites for the same company to observe from a user acceptance perspective.
B) A comparison of the performance of an ML system on two different input datasets.
C) A comparison of two different offers in a recommendation system to decide on the more effective offer for same users.
D) A comparison of the performance of two different ML implementations on the same input data.

3. A company producing consumable goods wants to identify groups of people with similar tastes for the purpose of targeting different products for each group. You have to choose and apply an appropriate ML type for this problem.
Which ONE of the following options represents the BEST possible solution for this above-mentioned task?
SELECT ONE OPTION

A) Regression
B) Association
C) Clustering
D) Classification

4. "BioSearch" is creating an Al model used for predicting cancer occurrence via examining X-Ray images. The accuracy of the model in isolation has been found to be good. However, the users of the model started complaining of the poor quality of results, especially inability to detect real cancer cases, when put to practice in the diagnosis lab, leading to stopping of the usage of the model.
A testing expert was called in to find the deficiencies in the test planning which led to the above scenario.
Which ONE of the following options would you expect to MOST likely be the reason to be discovered by the test expert?
SELECT ONE OPTION

A) A lack of focus on non-functional requirements testing.
B) A lack of similarity between the training and testing data.
C) The input data has not been tested for quality prior to use for testing.
D) A lack of focus on choosing the right functional-performance metrics.

Solutions: