시험대비CT-AI인기자격증덤프공부

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ISTQB CT-AI 시험요강:

주제소개
주제 1
  • ML Functional Performance Metrics: In this section, the topics covered include how to calculate the ML functional performance metrics from a given set of confusion matrices.
주제 2
  • 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.
주제 3
  • systems from those required for conventional systems.
주제 4
  • Test Environments for AI-Based Systems: This section is about factors that differentiate the test environments for AI-based
주제 5
  • Introduction to AI: This exam section covers topics such as the AI effect and how it influences the definition of AI. It covers how to distinguish between narrow AI, general AI, and super AI; moreover, the topics covered include describing how standards apply to AI-based systems.
주제 6
  • 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.
주제 7
  • Using AI for Testing: In this section, the exam topics cover categorizing the AI technologies used in software testing.
주제 8
  • 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.
주제 9
  • Quality Characteristics for AI-Based Systems: This section covers topics covered how to explain the importance of flexibility and adaptability as characteristics of AI-based systems and describes the vitality of managing evolution for AI-based systems. It also covers how to recall the characteristics that make it difficult to use AI-based systems in safety-related applications.
주제 10
  • Testing AI-Based Systems Overview: In this section, focus is given to how system specifications for AI-based systems can create challenges in testing and explain automation bias and how this affects testing.
주제 11
  • 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.

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CT-AI인기자격증 최신 인기시험 기출문제

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최신 ISTQB AI Testing CT-AI 무료샘플문제 (Q60-Q65):

질문 # 60
Which ONE of the following statements provides the BEST description of the AI effect?

정답：C

설명：
The correct answer is C because it directly describes the AI effect , where systems once classified as artificial intelligence cease to be regarded as AI after the technology becomes familiar, understood, or superseded. The CT-AI syllabus states that the changing perception of what constitutes AI is known as the "AI Effect," and explains that computer chess systems, including Deep Blue's victory over Garry Kasparov, were formerly viewed as AI but are no longer considered by many to be "true" AI because they used a brute-force approach rather than learning from data or self-learning. Appendix B reinforces this by defining the AI effect as the situation where a previously labelled AI system is no longer considered AI as technology advances.
Option A refers to technological singularity , which belongs to the distinction between general AI and super AI, not the AI effect. Option B describes adaptive or machine-learning behaviour, not a shift in social perception. Option D describes human-like behaviour, which is related to AI capability but not to reclassification over time.
References/topics: CT-AI Syllabus Chapter 1, Section 1.1 "Definition of AI and AI Effect"; Appendix B
"AI effect."


질문 # 61
Which of the following is an example of overfitting?

정답：A

설명：
The syllabus defines overfitting as:
"Overfitting is when the ML model learns the training data so well that it is unable to generalize to accommodate new data." This occurs when the model memorizes the training data, including noise, instead of learning the general patterns.
(Reference: ISTQB CT-AI Syllabus v1.0, Section 3.5.1, page 31 of 99)


질문 # 62
A team of software testers is attempting to create an AI algorithm to assist in software testing.
This particular team has gone through over 40 iterations of testing and cannot afford to spend as much time as it takes to run the full regression test suite. They are hoping to have the algorithm reduce the amount of testing required thus reducing the time needed for each testing cycle. How can an AI-based tool be expected to assist in this reduction?

정답：D

설명：
AI-based tools can significantly optimize regression test suites by analyzing historical data, past test results, associated defects, and changes made to the software. These tools prioritize and select the most relevant test cases based on previous defect patterns and frequently failing features, which helps in reducing the test execution time while maintaining effectiveness.


질문 # 63
You are testing an autonomous vehicle which uses AI to determine proper driving actions and responses. You have evaluated the parameters and combinations to be tested and have determined that there are too many to test in the time allowed. It has been suggested that you use pairwise testing to limit the parameters. Given the complexity of the software under test, what is likely the outcome from using pairwise testing?

정답：D

설명：
The syllabus states that while pairwise testing is effective at finding defects by reducing the number of test cases needed, the resulting test suite can still be extensive and require automation:
"Even the use of pairwise testing can result in extensive test suites... automation and virtual test environments often become necessary to allow the required tests to be run." (Reference: ISTQB CT-AI Syllabus v1.0, Section 9.2, Page 67 of 99)


질문 # 64
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?

정답：D

설명：
In the syllabus, theevolutioncharacteristic for AI-based systems means the ability of the system to evolve and adapt its behavior in response to changes in the environment or in its own performance:
"Evolution is the system's ability to change itself to adapt to new situations, different hardware, or a changing operational environment." (Reference: ISTQB CT-AI Syllabus v1.0, Section 2.3)


질문 # 65
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ISTQB CT-AI인증시험패스 하는 동시에 여러분의 인생에는 획기적인 일 발생한것이죠, 사업에서의 상승세는 당연한것입니다. IT업계종사자라면 누구나 이런 자격증을 취득하고싶어하리라고 믿습니다. 많은 분들이 이렇게 좋은 인증시험은 아주 어렵다고 생각합니다. 네 많습니다. 패스할확율은 아주 낮습니다. 노력하지않고야 당연히 불가능하죠.ISTQB CT-AI시험은 기초지식 그리고 능숙한 전업지식이 필요요 합니다. 우리KoreaDumps는 여러분들한테ISTQB CT-AI시험을 쉽게 빨리 패스할 수 있도록 도와주는 사이트입니다. 우리KoreaDumps의ISTQB CT-AI시험관련자료로 여러분은 짧은시간내에 간단하게 시험을 패스할수 있습니다. 시간도 절약하고 돈도 적게 들이는 이런 제안은 여러분들한테 딱 좋은 해결책이라고 봅니다.

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