Which practical consideration is more closely associated with predictive AI?

Preventing the model from producing offensive text

Verifying the originality of generated code

Managing the risk of bias in predictions that affect decisions

Ensuring generated images are not used to spread misinformation

Which evaluation metric is commonly used for predictive AI models?

Fréchet Inception Distance (FID)

A team has built a model to predict fraudulent transactions and another to generate realistic synthetic transaction data for training. Which evaluation metric is appropriate for the fraud detection model?

Realism, because it measures how realistic the fraud predictions are.

Precision, because it measures the proportion of predicted fraud cases that are actually fraudulent.

Diversity, because it measures the variety of generated transactions.

Creativity, because it measures the novelty of the fraud predictions.

An insurance company wants to identify which policyholders are likely to file a claim in the next quarter. They have historical claim records with policyholder attributes and claim outcomes. Which predictive technique is most appropriate?

Classification to predict whether a policyholder will file a claim.

Generative modeling to create new claim records.

Time-series forecasting to predict the number of claims per month.

Regression to predict the exact amount of the next claim.

NetAppCertified AI Expert

Domain 2Objective 1

Determine the Differences Between Predictive AI and Generative AI CERTIFIED-AI-EXPERT Practice Questions (Page 2)

Part of the AI Lifecycle domain, which accounts for 27% of the CERTIFIED-AI-EXPERT exam. NetApp does not publish an official question count, but from its 90-minute exam (~35–60 total, ~9–16 in this domain), expect 1–2 from this objective — we provide 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

11concepts

27%of the exam

11 Concepts in This Objective

Definition of predictive AI
Definition of generative AI
Core techniques in predictive AI
Core techniques in generative AI
Use cases for predictive AI
Use cases for generative AI
Data requirements comparison
Output nature comparison
Evaluation metrics comparison
Model complexity and training differences
Ethical and practical considerations

Questions 6–10

6foundation · easy
Which technique is primarily associated with predictive AI?
Select an answer first
7foundation · easy
Which practical consideration is more closely associated with predictive AI?
Select an answer first
8foundation · easy
Which evaluation metric is commonly used for predictive AI models?
Select an answer first
9application · medium
A team has built a model to predict fraudulent transactions and another to generate realistic synthetic transaction data for training. Which evaluation metric is appropriate for the fraud detection model?
Select an answer first
10application · medium
An insurance company wants to identify which policyholders are likely to file a claim in the next quarter. They have historical claim records with policyholder attributes and claim outcomes. Which predictive technique is most appropriate?
Select an answer first

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