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39. Frage
If humans are unlabeling the data and the machine is correctly labeling current or future data points, it's
______.
Antwort: B
Begründung:
Semi-supervised learning is the correct answer because it combines a small amount of labeled data with a larger amount of unlabeled data. In this scenario, humans are not fully labeling the data, but the machine is still able to correctly label current or future data points by learning patterns from the available data. That matches the concept of semi-supervised learning, where the model uses limited human-provided labels and extends learning to unlabeled examples.
Supervised learning is not the best answer because supervised learning depends on clearly labeled training data supplied by humans. Unsupervised learning is also incorrect because it identifies hidden patterns or clusters without using labels, rather than predicting correct labels for future data points. Reinforcement learning is based on rewards, penalties, actions, and an environment, which is not described here. "Semi- reinforcement learning" is not a standard main category in machine learning.
Therefore, the most accurate answer is **E. Semi-supervised learning**.
40. Frage
Which of the following is a CORRECT statement for the Data and AI Analytics Business Model Maturity Index?
Antwort: C
Begründung:
The correct answer is D. a and b only because the Data and AI Analytics Business Model Maturity Index is mainly used to guide and assess how effectively an organization uses data, analytics, and AI to improve business and operational models. Option A is correct because a maturity index provides a roadmap that helps organizations understand where they are currently and what capabilities they need to develop next. This supports better use of analytics, data-driven decision-making, and AI-enabled transformation.
Option B is also correct because a maturity index works as a benchmark. Organizations can compare their current maturity level against defined stages, measure progress, identify gaps, and evaluate improvement in analytics capabilities over time.
Option C is not the best statement because "focus on ROI and team" is too narrow and incomplete. ROI and team capability may be considered in analytics planning, but they do not fully define the purpose of the maturity index. Therefore, the best answer is D. a and b only .
41. Frage
Which of the CORRECT cognitive modeling is used in AI applications?
Antwort: C
Begründung:
The correct answer is E. All of the above because deep learning, expert systems, natural language processing, and robotics are all connected with AI applications that support or model intelligent behavior. Cognitive modeling in AI is concerned with building systems that can represent, simulate, or support human-like capabilities such as learning, reasoning, decision-making, perception, language understanding, and action.
Deep learning is used to recognize patterns from large amounts of data and is common in speech recognition, image analysis, recommendation systems, and generative AI. Expert systems use knowledge bases and rules to support decision-making in specialized domains. Natural language processing helps AI systems understand, interpret, generate, and respond to human language. Robotics applies AI to physical systems so machines can sense, plan, move, and perform tasks in real-world environments.
Since all the listed options are valid AI application areas related to intelligent and cognitive capabilities, the correct answer is E. All of the above .
42. Frage
Choose the CORRECT statement for GenAI.
Antwort: C
Begründung:
The correct answer is E. All of the above because all three statements describe the broader idea of general intelligence in AI systems. GenAI in this question is presented as intelligence that goes beyond narrow, task- specific AI and aims to support broader reasoning, learning, adaptation, and performance across multiple domains.
Statement A is correct because general AI focuses on systems that can demonstrate human-like cognitive abilities and perform different kinds of tasks rather than being limited to one predefined function. Statement B is also correct because architects working on such advanced AI systems must design solutions that go beyond specific use cases and support more general intelligence capabilities. Statement C is correct because general AI systems are expected to learn from limited data, transfer knowledge across domains, adapt to changing environments, and perform reliably in uncertain situations.
Since A, B, and C are all correct, the best answer is E. All of the above .
43. Frage
Choose the CORRECT statement for Naive Bayes classifier.
Antwort: D
Begründung:
The correct answer is D. a and c only . Naive Bayes is a supervised machine learning classification algorithm based on Bayes' theorem. It is called "naive" because it assumes that the features used for prediction are conditionally independent of one another, even though this may not always be fully true in real-world data.
Therefore, statement A is correct because the algorithm treats each feature as an independent variable when calculating class probabilities.
Statement C is also correct because Naive Bayes is commonly used for classification problems such as spam detection, where the model predicts whether an email is spam or not spam. It is also used in sentiment analysis, text classification, document categorization, and simple probabilistic classification tasks.
Statement B is not the best statement because the key idea is not about "unique features" specifically, but about the independence assumption applied to features. Therefore, the correct answer is D. a and c only .
44. Frage
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