CT-AI問題集、ISTQB実際の試験問題

質問 1

You have been asked for your opinion on the ML approach to be used for a new age verification system. A training dataset is available with many pictures of faces and the subject's age. When new users sign up to a mobile app, they have to take a picture of their face. If the system believes they are under 18 years old it will ask them to provide a picture of their passport to prove their age. Which ONE of the following approaches do you expect to be MOST likely to succeed?

A. Supervised learning regression system that is re trained based on new data, including whether they provided ID that showed their age.

B. Reinforcement learning classification system with a reward function of correct behaviour.

C. Unsupervised learning that identifies clusters in training data that relate to people's ages.

D. Supervised learning classification system that is re-trained based on new data, including whether they later provided ID that showed they were over 18.

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 2

Which ONE of the following hardware is MOST suitable for implementing Al when using ML?
SELECT ONE OPTION

A. Hardware supporting fast matrix multiplication.

B. High powered CPUs.

C. 64-bit CPUs.

D. Hardware supporting high precision floating point operations.

正解: A

解説: (PassTest メンバーにのみ表示されます)

質問 3

Which ONE of the following is the BEST option to optimize the regression test selection and prevent the regression suite from growing large?
SELECT ONE OPTION

A. Identifying suitable tests by looking at the complexity of the test cases.

B. Using of a random subset of tests.

C. Automating test scripts using Al-based test automation tools.

D. Using an Al-based tool to optimize the regression test suite by analyzing past test results

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 4

Consider an AI-system in which the complex internal structure has been generated by another software system. Why would the tester choose to do black-box testing on this particular system?

A. Black-box testing eliminates the need for the tester to understand the internal structure of the AI-system

B. The tester wishes to better understand the logic of the software used to create the internal structure

C. The black-box testing method will allow the tester to check the transparency of the algorithm used to create the internal structure

D. Test automation can be built quickly and easily from the test cases developed during black-box testing

正解: A

解説: (PassTest メンバーにのみ表示されます)

質問 5

Which statement regarding data preparation in the ML workflow is correct?
Choose ONE option (1 out of 4)

A. One challenge of data gathering is obtaining high-quality data from multiple sources.

B. Sampling is so well researched that it is no longer considered risky.

C. Since data preparation is time-consuming, all steps should be automated.

D. A key challenge in data transformation is the removal or correction of erroneous data.

正解: A

解説: (PassTest メンバーにのみ表示されます)

質問 6

A local business has a mail pickup/delivery robot for their office. The robot currently uses a track to move between pickup/drop-off locations. When it arrives at a destination, the robot stops to allow a human to remove or deposit mail. The office has decided to upgrade the robot to include AI capabilities that allow the robot to perform its duties without a track, without running into obstacles, and without human intervention.
The test team is creating a list of new and previously established test objectives and acceptance criteria to be used in the testing of the robot upgrade. Which of the following test objectives will test an AI quality characteristic for this system?

A. The robot must complete 99.99% of its deliveries each day

B. The robot must record the time of each delivery which is compiled into a report

C. The robot must recharge for no more than six hours a day

D. The robot must evolve to optimize its routing

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 7

Which of the following statements regarding experience-based testing for AI-based systems is correct?
Choose ONE option (1 out of 4)

A. In checklist-based testing of AI-based systems, the existing test cases are dynamically adapted, for example based on metamorphic testing.

B. Exploratory testing is often used for AI-based systems because there are often insufficient specifications or problems with the test oracle for AI-based systems.

C. Intuitive test case design for AI-based systems involves interactive, hypothesis-driven examination of data for correlations or developmental trends.

D. Tour refers to intuitive test case design for AI-based systems based on multiple, sequential test cases using systematically biased training data.

正解: B

解説: (PassTest メンバーにのみ表示されます)

質問 8

A tourist calls an airline to book a ticket and is connected with an automated system which is able to recognize speech, understand requests related to purchasing a ticket, and provide relevant travel options.
When the tourist asks about the expected weather at the destination or potential impacts on operations because of the tight labor market, the only response from the automated system is, "I don't understand your question." This AI system should be categorized as?

A. Narrow AI

B. General AI

C. Conventional AI

D. Super AI

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 9

You are evaluating the use of a highly accurate pre trained model that is used widely in industry tor a similar use case. There is an intention to apply transfer learning techniques to further customise the model. Which ONE of the following is the LEAST likely to be a significant risk with this approach?

A. Differences in data preparation steps between the training of the pre-trained model and consequent use of the model may result in reduced functional performance

B. The system may be vulnerable to adversarial attacks inherited from the pre trained model

C. The functional performance of the pre trained model could be lower than stakeholders expect

D. The functional performance of the system may exhibit bias

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 10

A bank wants to use an algorithm to determine which applicants should be given a loan. The bank hires a data scientist to construct a logistic regression model to predict whether the applicant will repay the loan or not.
The bank has enough data on past customers to randomly split the data into a training dataset and a test
/validation dataset. A logistic regression model is constructed on the training dataset using the following independent variables:
Gender
Marital status
Number of dependents
Education
Income
Loan amount
Loan term
Credit score
The model reveals that those with higher credit scores and larger total incomes are more likely to repay their loans. The data scientist has suggested that there might be bias present in the model based on previous models created for other banks.
Given this information, what is the best test approach to check for potential bias in the model?

A. A/B testing should be used to verify that the test data set does not detect any bias that might have been introduced by the original training data. If the two models significantly differ, it will indicate there is bias in the original model.

B. Acceptance testing should be used to make sure the algorithm is suitable for the customer. The team can re-work the acceptance criteria such that the algorithm is sure to correctly predict the remaining applicants that have been set aside for the validation dataset ensuring no bias is present.

C. Experience-based testing should be used to confirm that the training data set is operationally relevant.
This can include applying exploratory data analysis (EDA) to check for bias within the training data set.

D. Back-to-back testing should be used to compare the model created using the training data set to another model created using the test data set. If the two models significantly differ, it will indicate there is bias in the original model.

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 11

Which ONE of the following options describes a scenario of A/B testing the LEAST?
SELECT ONE OPTION

A. A comparison of the performance of an ML system on two different input datasets.

B. A comparison of the performance of two different ML implementations on the same input data.

C. A comparison of two different websites for the same company to observe from a user acceptance perspective.

D. A comparison of two different offers in a recommendation system to decide on the more effective offer for same users.

正解: A

解説: (PassTest メンバーにのみ表示されます)

質問 12

Which machine learning approach is most suitable for predicting customer purchase probability?
Choose ONE option (1 out of 4)

A. Unsupervised learning

B. Supervised learning (regression)

C. Reinforcement learning

D. Supervised learning (classification)

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 13

Which of the following is one of the reasons for data mislabelling?

A. Interoperability error

B. Expert knowledge

C. Small datasets

D. Lack of domain knowledge

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 14

Which statement describes factors related to test data that make testing AI-based systems difficult?
Choose ONE option (1 out of 4)

A. Using the same implementation for data acquisition by data scientists and testers prevents defect masking

B. The input data must always be the same over time, especially in real-world systems

C. Artificially generated data requires legal approval and must be sanitized and encrypted

D. Creating and managing large amounts of test data can be difficult, especially when it needs to be representative

正解: D

解説: (PassTest メンバーにのみ表示されます)

ISTQB Certified Tester AI Testing - CT-AI 模擬練習