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

1. In a conference on artificial intelligence (Al), a speaker made the statement, "The current implementation of Al using models which do NOT change by themselves is NOT true Al*. Based on your understanding of Al, is this above statement CORRECT or INCORRECT and why?
SELECT ONE OPTION

A) This statement is correct. In general, what is considered Al today may change over time.
B) This statement is incorrect. What is considered Al today will continue to be Al even as technology evolves and changes.
C) This statement is correct. In general, today the term Al is utilized incorrectly.
D) This statement is incorrect. Current Al is true Al and there is no reason to believe that this fact will change over time.

2. Which ONE of the following activities is MOST relevant when addressing the scenario where you have more than the required amount of data available for the training?
SELECT ONE OPTION

A) Data labeling
B) Data sampling
C) Feature selection
D) Data augmentation

3. Which ONE of the following combinations of Training, Validation, Testing data is used during the process of learning/creating the model?
SELECT ONE OPTION

A) Training data - validation data
B) Training data * test data
C) Validation data - test data
D) Training data - validation data - test data

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

Solutions: