ISTQB CT-AI Exam Syllabus Topics:

Topic	Details
Topic 1	Methods and Techniques for the Testing of AI-Based Systems: In this section, the focus is on explaining how the testing of ML systems can help prevent adversarial attacks and data poisoning.
Topic 2	Test Environments for AI-Based Systems: This section is about factors that differentiate the test environments for AI-based
Topic 3	Neural Networks and Testing: This section of the exam covers defining the structure and function of a neural network including a DNN and the different coverage measures for neural networks.
Topic 4	Using AI for Testing: In this section, the exam topics cover categorizing the AI technologies used in software testing.
Topic 5	Machine Learning ML: This section includes the classification and regression as part of supervised learning, explaining the factors involved in the selection of ML algorithms, and demonstrating underfitting and overfitting.
Topic 6	Testing AI-Specific Quality Characteristics: In this section, the topics covered are about the challenges in testing created by the self-learning of AI-based systems.

Reference: https://www.istqb.org/certifications/artificial-inteligence-tester

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ISTQB Certified Tester AI Testing Sample Questions:

Question #1

Which ONE of the following options is an example that BEST describes a system with Al-based autonomous functions?
SELECT ONE OPTION

A. A system that utilizes a tool like Selenium.
B. A fully automated manufacturing plant that uses no software.
C. A system that utilizes human beings for all important decisions.
D. A system that is fully able to respond to its environment.

Reveal Solution Discussion 0

Correct Answer: D 🗳️

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Question #2

Data used for an object detection ML system was found to have been labelled incorrectly in many cases.
Which ONE of the following options is most likely the reason for this problem?
SELECT ONE OPTION

A. Bias issues
B. Accuracy issues
C. Security issues
D. Privacy issues

Reveal Solution Discussion 0

Correct Answer: B 🗳️

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Question #3

Which of the following is an example of an input change where it would be expected that the AI system should be able to adapt?

A. It has been trained to analyze mathematical models and is given a set of landscape pictures to classify
B. It has been trained to recognize human faces at a particular resolution and it is given a human face image captured with a higher resolution
C. It has been trained to analyze customer buying trend data and is given information on supplier cost data
D. It has been trained to recognize cats and is given an image of a dog

Reveal Solution Discussion 0

Correct Answer: B 🗳️

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Question #4

Which ONE of the following statements is true about dynamic testing for inappropriate bias?

A. Testing should never be conducted in production
B. It can be necessary to obtain additional attributes about the data being processed
C. Inappropriate bias only needs to be tested when protected characteristics such as race and gender ate present in the inputs
D. Reviewing the source of the training data can reveal inappropriate bias

Reveal Solution Discussion 0

Correct Answer: B 🗳️

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Question #5

A robotic AI based system is being built by a logistics company to operate within its unmanned warehouses.
The warehouses can all be very different and new ones are being added each year. It is expected that the system will not require retraining for each warehouse, and will be able to learn the location of different items and move them to specified locations on request. Which ONE of the following attributes should be MOST carefully considered when specifying the objectives and acceptance criteria for the system?