ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
1. Which ONE of the following options represents a technology MOST TYPICALLY used to implement Al?
SELECT ONE OPTION
A) Genetic algorithms
B) Case control structures
C) Procedural programming
D) Search engines
2. 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) Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.
D) Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
3. Which ONE of the following characteristics is the least likely to cause safety related issues for an Al system?
SELECT ONE OPTION
A) Robustness
B) High complexity
C) Self-learning
D) Non-determinism
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:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: B |
We're so confident of our products that we provide no hassle product exchange.


By Hedda

