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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

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

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

2. Pairwise testing can be used in the context of self-driving cars for controlling an explosion in the number of combinations of parameters.
Which ONE of the following options is LEAST likely to be a reason for this incredible growth of parameters?
SELECT ONE OPTION

A) ML model metrics to evaluate the functional performance
B) Different features like ADAS, Lane Change Assistance etc.
C) Different weather conditions
D) Different Road Types

3. In a certain coffee producing region of Colombia, there have been some severe weather storms, resulting in massive losses in production. This caused a massive drop in stock price of coffee.
Which ONE of the following types of testing SHOULD be performed for a machine learning model for stock-price prediction to detect influence of such phenomenon as above on price of coffee stock.
SELECT ONE OPTION

A) Testing for concept drift
B) Testing for bias
C) Testing for accuracy
D) Testing for security

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

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

Solutions: