CT-AI시험패스인증덤프 & CT-AI최고품질덤프문제보기

참고: PassTIP에서 Google Drive로 공유하는 무료 2026 ISTQB CT-AI 시험 문제집이 있습니다: https://drive.google.com/open?id=1a5tFNbRD8WrncHBfbXXZbSNoKBcim9IO

PassTIP 에서ISTQB CT-AI 덤프를 구매하시면 일년무료 업데이트서비스를 받을수 있습니다.일년무료 업데이트서비스란 구매일로부터 1년동안 구매한 덤프가 업데이트될때마다 구매시 사용한 메일주소로 가장 최신버전을 보내드리는것을 의미합니다. ISTQB CT-AI덤프에는 가장 최신시험문제의 기출문제가 포함되어있어 높은 적주율을 자랑하고 있습니다.

ISTQB CT-AI 시험요강:

주제	소개
주제 1	systems from those required for conventional systems.
주제 2	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 3	ML: Data: This section of the exam covers explaining the activities and challenges related to data preparation. It also covers how to test datasets create an ML model and recognize how poor data quality can cause problems with the resultant ML model.
주제 4	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 5	Test Environments for AI-Based Systems: This section is about factors that differentiate the test environments for AI-based
주제 6	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 7	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 8	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.
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	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.

>> CT-AI시험패스 인증덤프 <<

CT-AI최고품질 덤프문제보기 & CT-AI시험패스 가능한 공부

지난 몇년동안 IT산업의 지속적인 발전과 성장을 통해ISTQB 인증CT-AI시험은 IT인증시험중의 이정표로 되어 많은 인기를 누리고 있습니다. IT인증시험을PassTIP덤프로 준비해야만 하는 이유는PassTIP덤프는 IT업계전문가들이 실제시험문제를 연구하여 시험문제에 대비하여 예상문제를 제작했다는 점에 있습니다.

최신 ISTQB AI Testing CT-AI 무료샘플문제 (Q104-Q109):

질문 # 104
Which ONE of the following statements is true about dynamic testing for inappropriate bias?

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

정답：A

설명：
The correct answer is A . Dynamic testing for inappropriate bias may require testers to obtain additional attributes about the input data so that outcomes can be analyzed across relevant groups. The CT-AI syllabus explains that testers may need additional information about attributes potentially related to bias and then correlate those attributes with system results. This is particularly important where bias is based on "hidden" variables that are not explicitly present in the input data but are inferred by the algorithm.
Option B is partly relevant to static testing or review activity, but the question asks specifically about dynamic testing . Option C is incorrect because inappropriate bias may be present even when protected attributes are not explicit model inputs; the model may infer them indirectly from proxy variables. Option D is also incorrect because the syllabus states that measuring how changes in inputs affect outputs for bias-related groups may be performed in production as well as before release. Therefore, obtaining and correlating additional attributes is a valid and often necessary dynamic testing activity.
References/topics: CT-AI Syllabus Chapter 8, Section 8.3 "Testing for Algorithmic, Sample and Inappropriate Bias."
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질문 # 105
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

A. Aspects I, IV, and V
B. Aspects III, IV, and V
C. Aspects II, III and IV
D. Aspects I, II, and III

정답：B

설명：
For AI-enabled medical devices, the most required aspects for certification are safety, transparency, and side effects. Here's why:
* Safety (Aspect III): Critical for ensuring that the AI system does not cause harm to patients.
* Transparency (Aspect IV): Important for understanding and verifying the decisions made by the AI system.
* Side Effects (Aspect V): Necessary to identify and mitigate any unintended consequences of the AI system.
Why Not Other Options:
* Autonomy and Maintainability (Aspects I and II): While important, they are secondary to the immediate concerns of safety, transparency, and managing side effects in life-critical processes.
References:This explanation is aligned with the critical quality characteristics for AI-based systems as mentioned in the ISTQB CT-AI syllabus, focusing on the certification of medical devices.

질문 # 106
Which statement about using AI to analyze reported defects is MOST correct?

A. ML models can support duplicate defect identification when checking defect criticality.
B. ML models identify developers who should handle a defect based on ticket content.
C. ML models can identify categories for a reported defect during assignment.
D. ML models trained with critical defect tickets can identify defects that cause serious consequences.

정답：C

설명：
The ISTQB CT-AI syllabus (Section5.3 - AI Support for Defect Analysis) explains that AI can categorize defect reports using natural language processing or classification models.
Categorization helps route defects efficiently and determine which areas of the system are affected. Thus, Option C is correct: AI canidentify defect categories, supporting assignment and triage.

질문 # 107
A beer company is trying to understand how much recognition its logo has in the market. It plans to do that by monitoring images on various social media platforms using a pre-trained neural network for logo detection. This particular model has been trained by looking for words, as well as matching colors on social media images. The company logo has a big word across the middle with a bold blue and magenta border. Which associated risk is most likely to occur when using this pre-trained model?

A. Improper data preparation
B. Insufficient function; the model was not trained to check for colors or words
C. There is no risk, as the model has already been trained
D. Inherited bias: the model could have inherited unknown defects

정답：D

설명：
According to the syllabus, pre-trained models often inherit biases and limitations from the data and processes used in their original training, which may not align with the new use case.
Specifically, the syllabus states:
"When using a pre-trained model, the training data and process cannot be fully controlled or known by the user of the model. As a result, the model can inherit biases or inaccuracies that were part of its original development and training process."

질문 # 108
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 customer buying trend data and is given information on supplier cost data
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 mathematical models and is given a set of landscape pictures to classify
D. It has been trained to recognize cats and is given an image of a dog

정답：B

설명：
The syllabus explains that input changes that arein the same domainas what was used for training are expected to be handled with adaptability:
"Adaptability refers to the ability of a system to adjust its behavior in response to changes in its environment or inputs. This includes changes to the inputs which are still within the expected operational range of the system, such as resolution changes in images or sensor data." (Reference: ISTQB CT-AI Syllabus v1.0, Section 7.6 and 8.2)

질문 # 109
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ISTQB CT-AI시험이 정말 어렵다는 말을 많이 들으신 만큼 저희 PassTIP는ISTQB CT-AI덤프만 있으면ISTQB CT-AI시험이 정말 쉬워진다고 전해드리고 싶습니다. ISTQB CT-AI덤프로 시험패스하고 자격증 한방에 따보세요. 자격증 많이 취득하면 더욱 여유롭게 직장생활을 즐길수 있습니다.

CT-AI최고품질 덤프문제보기: https://www.passtip.net/CT-AI-pass-exam.html

BONUS!!! PassTIP CT-AI 시험 문제집 전체 버전을 무료로 다운로드하세요: https://drive.google.com/open?id=1a5tFNbRD8WrncHBfbXXZbSNoKBcim9IO