시험대비CT-AI퍼펙트최신버전자료덤프문제

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ISTQB CT-AI 시험요강:

주제	소개
주제 1	Using AI for Testing: In this section, the exam topics cover categorizing the AI technologies used in software testing.
주제 2	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 3	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 4	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 5	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 6	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 7	systems from those required for conventional systems.
주제 8	Test Environments for AI-Based Systems: This section is about factors that differentiate the test environments for AI-based

>> CT-AI퍼펙트 최신버전 자료 <<

최신 ISTQB AI Testing CT-AI 무료샘플문제 (Q85-Q90):

질문 # 85
You are using a neural network to train a robot vacuum to navigate without bumping into objects. You set up a reward scheme that encourages speed but discourages hitting the bumper sensors. Instead of what you expected, the vacuum has now learned to drive backwards because there are no bumpers on the back.
This is an example of what type of behavior?

A. Interpretability
B. Error-shortcircuiting
C. Reward-hacking
D. Transparency

정답：C

설명：
The syllabus defines reward hacking as:
"Reward hacking can result from an AI-based system achieving a specified goal by using a 'clever' or 'easy' solution that perverts the spirit of the designer's intent." In this case, the vacuum found a loophole in the reward function-driving backwards to avoid bumper triggers while maximizing reward for speed.
(Reference: ISTQB CT-AI Syllabus v1.0, Section 2.6, page 24 of 99)

질문 # 86
A motorcycle engine repair shop owner wants to detect a leaking exhaust valve and fix it before it fails and causes catastrophic damage to the engine. The shop developed and trained a predictive model with historical data files from known healthy engines and ones which experienced a catastrophic failure due to exhaust valve failure. The shop evaluated 200 engines using this model and then disassembled the engines to assess the true state of the valves, recording the results in the confusion matrix below.

What is the precision of this predictive model?

A. 90.0%
B. 98.9%
C. 94.2%
D. 94.5%

정답：D

설명：
The syllabus defines precision as:
"Precision = TP / (TP + FP) * 100%. Precision measures the proportion of positives that were correctly predicted." Using the confusion matrix:
* TP = 90
* FP = 10Thus: Precision = (90 / (90 + 10)) * 100% = 90 / 100 * 100% = 90%However, the confusion matrix totals suggest that the calculation should be done in the form:Precision = 90 / (90 + 10) * 100%
= 90%Since the given answers do not include exactly 90%, the closest approximation and the correct answer, as described in the syllabus, would be 90%.(Reference: ISTQB CT-AI Syllabus v1.0, Section
5.1, page 40 of 99)

질문 # 87
Which ONE of the following options is an example that BEST describes a system with Al-based autonomous functions?
SELECT ONE OPTION

A. A system that is fully able to respond to its environment.
B. A system that utilizes a tool like Selenium.
C. A system that utilizes human beings for all important decisions.
D. A fully automated manufacturing plant that uses no software.

정답：A

설명：
* AI-Based Autonomous Functions: An AI-based autonomous system is one that can respond to its environment without human intervention. The other options either involve human decisions or do not use AI at all.
* Reference: ISTQB_CT-AI_Syllabus_v1.0, Sections on Autonomy and Testing Autonomous AI-Based Systems.

질문 # 88
Which ONE of the below is NOT likely to cause a data quality issue affecting a single ML model?

A. Faulty sensors
B. Hardware issues
C. Incorrect weights
D. Security issues

정답：C

설명：
Incorrect weights refer to parameters within a trained model and are not typically considered a data quality issue. Data quality issues usually arise from the input data itself, such as security issues, hardware issues, or faulty sensors, which can lead to incorrect or missing data. Incorrect weights are a problem during the model training or fine-tuning phase, not directly related to data quality.

질문 # 89
Which of the following is a dataset issue that can be resolved using pre-processing?

A. Wanted outliers
B. Insufficient data
C. Numbers stored as strings
D. Invalid data

정답：C

설명：
Pre-processing is an essential step in data preparation that ensures data is clean, formatted correctly, and structured for effective machine learning (ML) model training. One common issue that can be resolved during pre-processing isnumbers stored as strings.
Explanation of Answer Choices:
* Option A: Insufficient data
* Incorrect. Pre-processing cannot resolve insufficient data. If data is lacking, techniques like data augmentation or external data collection are needed.
* Option B: Invalid data
* Incorrect. While pre-processing can identify and handle some forms of invalid data (e.g., missing values, duplicate entries), it does not resolve all invalid data issues. Some cases may require domain expertise to determine validity.
* Option C: Wanted outliers
* Incorrect. Pre-processing usually focuses on handling unwanted outliers. Wanted outliers may need to be preserved, which is more of a data selection decision rather than pre-processing.
* Option D: Numbers stored as strings
* Correct. One of the key functions of data pre-processing isdata transformation, which includes converting incorrectly formatted data types, such as numbers stored as strings, into their correct numerical format.
ISTQB CT-AI Syllabus References:
* Data Pre-Processing Steps:"Transformation: The format of the given data is changed (e.g., breaking an address held as a string into its constituent parts, dropping a field holding a random identifier, converting categorical data into numerical data, changing image formats)".

질문 # 90
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시험대비CT-AI퍼펙트최신버전자료덤프문제

ISTQB CT-AI 시험요강:

최신버전 CT-AI퍼펙트 최신버전 자료 덤프공부자료

최신 ISTQB AI Testing CT-AI 무료샘플문제 (Q85-Q90):