ISTQB CT-AI Certification Dumps (V8.02) – Best CT-AI Learning Materials for Certified Tester AI Testing Exam Preparation

Many professionals want to complete the ISTQB Certified Tester AI Testing (CT-AI) certification to extend their understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI-based systems and using AI in testing. Although taking the CT-AI exam is challenging, proper preparation can make this task manageable. DumpsBase’s ISTQB CT-AI certification dumps (V8.02) are available online to be your best study materials. Our experts have prepared the CT-AI exam questions and verified the answers according to the latest and actual syllabus of the ISTQB Certified Tester AI Testing certification exam. DumpsBase provides the latest CT-AI dumps that will help you understand the real ISTQB CT-AI test format. To ensure efficient preparation for the prestigious ISTQB Certified Tester AI Testing (CT-AI) exam, you should find the best CT-AI study materials. DumpsBase confirms the validity of its ISTQB CT-AI dumps with its great features.

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1. 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

2. Written requirements are given in text documents, which ONE of the following options is the BEST way to generate test cases from these requirements? SELECT ONE OPTION

3. A software component uses machine learning to recognize the digits from a scan of handwritten numbers.

In the scenario above, which type of Machine Learning (ML) is this an example of? SELECT ONE OPTION

4. Max. Score: 2

Al-enabled medical devices are used nowadays for automating certain parts of the medical diagnostic processes. Since these are life-critical process the relevant authorities are considenng bringing about suitable certifications for these Al enabled medical devices. This certification may involve several facets of Al testing (I - V).

I. Autonomy

II. Maintainability

III. Safety

IV. Transparency

V. Side Effects

Which ONE of the following options contains the three MOST required aspects to be satisfied for the above scenario of certification of Al enabled medical devices? SELECT ONE OPTION

5. Which ONE of the following options represents a technology MOST TYPICALLY used to implement Al? SELECT ONE OPTION

6. Which ONE of the following approaches to labelling requires the least time and effort? SELECT ONE OPTION

7. 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

8. Which ONE of the following types of coverage SHOULD be used if test cases need to cause each neuron to achieve both positive and negative activation values? SELECT ONE OPTION

9. Which ONE of the following describes a situation of back-to-back testing the LEAST? SELECT ONE OPTION

A. Comparison of the results of a current neural network model ML model implemented in platform A (for example Pytorch) with a similar neural network model ML model implemented in platform B (for example Tensorflow), for the same data.

B. Comparison of the results of a home-grown neural network model ML model with results in a neural network model implemented in a standard implementation (for example Pytorch) for same data

C. Comparison of the results of a neural network ML model with a current decision tree ML model for the same data.

D. Comparison of the results of the current neural network ML model on the current data set with a slightly modified data set.

10. Which ONE of the following options does NOT describe an Al technology related characteristic which differentiates Al test environments from other test environments? SELECT ONE OPTION

A. Challenges resulting from low accuracy of the models.

B. The challenge of mimicking undefined scenarios generated due to self-learning

C. The challenge of providing explainability to the decisions made by the system.

D. Challenges in the creation of scenarios of human handover for autonomous systems.


 

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