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| Section | Objectives |
|---|---|
| AI Fundamentals and Data Systems | - Fundamentals of Artificial Intelligence and Machine Learning - Developing and deploying data systems related to AI |
| Deployment and Maintenance | - Development, deployment, testing, and maintenance of AI applications |
| Neural Networks and Technical Applications | - Designing, developing, and troubleshooting technical applications on neural networks - Enhancing approaches to problems such as translation, speech recognition, and image classification |
| AI Solutions and Workflows | - Fraud prevention with Cloud AI solutions - Sentiment analysis - Advanced robotics - AI workflows |
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NEW QUESTION # 33
Supervised learning is a type of machine learning where the algorithm learns from a ______.
Answer: C
Explanation:
The correct answer is A. labeled dataset . Supervised learning is a machine learning method in which an algorithm is trained using data that already contains the correct output labels or target values. Each training example includes input features and a known answer, allowing the model to learn the relationship between the inputs and the expected output. Once trained, the model can use that learned relationship to classify or predict outcomes for new data.
An unlabeled dataset is used in unsupervised learning, where the model identifies hidden patterns, clusters, or relationships without predefined labels. An "explained dataset" is not a standard machine learning category.
Option D is incorrect because supervised learning does not learn from both labeled and unlabeled datasets as its primary definition. Option E is also incorrect because "explained dataset" is not the correct term.
Therefore, supervised learning learns from a labeled dataset , making A the correct answer.
NEW QUESTION # 34
Select the most CORRECT risk-scoring methodology function statement for prospective risk.
Answer: E
Explanation:
The correct answer is C because prospective risk is forward-looking. It focuses on estimating future model risk by using the most current risk condition, present indicators, and existing risk posture of the model. In AI governance and model risk management, prospective risk assessment helps organizations anticipate possible future issues such as performance degradation, bias, drift, compliance exposure, operational failure, or business impact before those risks become actual problems.
Option A is not the most correct because analyzing historical model performance is more closely linked with retrospective risk assessment. Historical performance can support risk analysis, but it does not fully define prospective risk. Option B is not accurate because "upcoming model performance" is not directly available for analysis; future performance must be predicted, not already analyzed. Option E is incorrect because A and B are not both accurate statements. Therefore, the most correct statement is C. Prospective risk leverages the most current risk of the model to predict the overall model risk for future cycles .
NEW QUESTION # 35
Which of the following is a CORRECT statement for the Data and AI Analytics Business Model Maturity Index?
Answer: C
Explanation:
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 .
NEW QUESTION # 36
Which type of AI mimics the human brain by building networks of artificial neurons?
Answer: B
Explanation:
The correct answer is C. Neural Networks . Neural networks are AI and machine learning models inspired by the structure and function of the human brain. They are built using interconnected artificial neurons, also called nodes, which process input data, apply weights and activation functions, and pass information through layers to produc e an output. This structure allows neural networks to learn complex patterns from data.
Fuzzy logic is incorrect because it deals with reasoning under uncertainty using degrees of truth rather than artificial neurons. Genetic algorithms are optimization methods inspired by natural selection and evolution, not the brain's neuron-based structure. Expert systems use rules and knowledge bases to make decisions, but they do not mimic the brain through networks of artificial neurons. Since the question specifically asks about AI that mimics the human brain by building artificial neuron networks, the correct answer is C. Neural Networks .
NEW QUESTION # 37
Which of the following is a regulatory requirement?
Answer: A
Explanation:
The correct answer is E. a, b and c only because HIPAA, GDPR, and CCPA are all regulatory requirements that organizations may need to follow when collecting, processing, storing, sharing, or protecting data. In AI and data-driven business environments, regulatory compliance is important because AI systems often depend on large volumes of personal, sensitive, customer, health, or behavioral data.
HIPAA is a United States healthcare regulation that protects sensitive patient health information. GDPR is a European Union data protection regulation that governs personal data processing, privacy rights, consent, data minimization, and accountability. CCPA is a California privacy law that gives consumers rights related to personal information, including access, deletion, and opt-out rights. These regulations affect how organizations design AI systems, manage data governance, ensure privacy, reduce risk, and maintain responsible AI practices.
Since all three listed items are valid regulatory requirements, the correct answer is E. a, b and c only .
NEW QUESTION # 38
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