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ISQI ISTQB Certified Tester AI Testing (v1.0) 認定 CT-AI_v1.0_World 試験問題 (Q10-Q15):

質問 # 10
Which ONE of the following activities is MOST relevant when addressing the scenario where you have more than the required amount of data available for the training?
SELECT ONE OPTION

A. Feature selection
B. Data labeling
C. Data augmentation
D. Data sampling

正解：D

解説：
* A. Feature selection
* Feature selection is the process of selecting the most relevant features from the data. While important, it is not directly about handling excess data.
* B. Data sampling
* Data sampling involves selecting a representative subset of the data for training. When there is more data than needed, sampling can be used to create a manageable dataset that maintains the statistical properties of the full dataset.
* C. Data labeling
* Data labeling involves annotating data for supervised learning. It is necessary for training models but does not address the issue of having excess data.
* D. Data augmentation
* Data augmentation is used to increase the size of the training dataset by creating modified versions of existing data. It is useful when there is insufficient data, not when there is excess data.
Therefore, the correct answer isBbecause data sampling is the most relevant activity when dealing with an excess amount of data for training.

質問 # 11
Which ONE of the following options BEST DESCRIBES clustering?
SELECT ONE OPTION

A. Clustering is done without prior knowledge of output classes.
B. Clustering requires you to know the classes.
C. Clustering is supervised learning.
D. Clustering is classification of a continuous quantity.

正解：A

解説：
Clustering is a type of machine learning technique used to group similar data points into clusters. It is a key concept in unsupervised learning, where the algorithm tries to find patterns or groupings in data without prior knowledge of output classes. Let's analyze each option:
* A. Clustering is classification of a continuous quantity.
* This is incorrect. Classification typically involves discrete categories, whereas clustering involves grouping similar data points. Classification of continuous quantities is generally referred to as regression.
* B. Clustering is supervised learning.
* This is incorrect. Clustering is an unsupervised learning technique because it does not rely on labeled data.
* C. Clustering is done without prior knowledge of output classes.
* This is correct. In clustering, the algorithm groups data points into clusters without any prior knowledge of the classes. It discovers the inherent structure in the data.
* D. Clustering requires you to know the classes.
* This is incorrect. Clustering does not require prior knowledge of classes. Instead, it aims to identify and form the classes or groups based on the data itself.
Therefore, the correct answer isCbecause clustering is an unsupervised learning technique done without prior knowledge of output classes.

質問 # 12
Which ONE of the following approaches to labelling requires the least time and effort?
SELECT ONE OPTION

A. Al-Assisted
B. Pre-labeled dataset
C. Outsourced
D. Internal

正解：B

解説：
Labelling Approaches:Among the options provided, pre-labeled datasets require the least time and effort because the data has already been labeled, eliminating the need for further manual or automated labeling efforts.
Reference:ISTQB_CT-AI_Syllabus_v1.0, Section 4.5 Data Labelling for Supervised Learning, which discusses various approaches to data labeling, including pre-labeled datasets, and their associated time and effort requirements.

質問 # 13
Which ONE of the following statements correctly describes the importance of flexibility for Al systems?
SELECT ONE OPTION

A. Flexible Al systems allow for easier modification of the system as a whole.
B. Self-learning systems are expected to deal with new situations without explicitly having to program for it.
C. Al systems require changing of operational environments; therefore, flexibility is required.
D. Al systems are inherently flexible.

正解：A

解説：
Flexibility in AI systems is crucial for various reasons, particularly because it allows for easier modification and adaptation of the system as a whole.
* AI systems are inherently flexible (A): This statement is not correct. While some AI systems may be designed to be flexible, they are not inherently flexible by nature. Flexibility depends on the system's design and implementation.
* AI systems require changing operational environments; therefore, flexibility is required (B): While it's true that AI systems may need to operate in changing environments, this statement does not directly address the importance of flexibility for the modification of the system.
* Flexible AI systems allow for easier modification of the system as a whole (C): This statement correctly describes the importance of flexibility. Being able to modify AI systems easily is critical for their maintenance, adaptation to new requirements, and improvement.
* Self-learning systems are expected to deal with new situations without explicitly having to program for it (D): This statement relates to the adaptability of self-learning systems rather than their overall flexibility for modification.
Hence, the correct answer isC. Flexible AI systems allow for easier modification of the system as a whole.
References:
* ISTQB CT-AI Syllabus Section 2.1 on Flexibility and Adaptability discusses the importance of flexibility in AI systems and how it enables easier modification and adaptability to new situations.
* Sample Exam Questions document, Question #30 highlights the importance of flexibility in AI systems.

質問 # 14
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 II, III and IV
B. Aspects III, IV, and V
C. Aspects I, II, and III
D. Aspects I, IV, and V

正解：B

解説：
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.

質問 # 15
......

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CT-AI_v1.0_World試験の準備方法｜権威のあるCT-AI_v1.0_World認定試験トレーリング試験｜高品質なISTQB Certified Tester AI Testing (v1.0)ウェブトレーニング

CT-AI_v1.0_Worldウェブトレーニング、CT-AI_v1.0_World資格参考書

ISQI ISTQB Certified Tester AI Testing (v1.0) 認定 CT-AI_v1.0_World 試験問題 (Q10-Q15):

試験の準備方法-100％合格率のCT-AI_v1.0_World認定試験トレーリング試験-有効的なCT-AI_v1.0_Worldウェブトレーニング

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