Free Isaca AI-Fundamentals Exam Questions

Become Isaca Certified with updated AI-Fundamentals exam questions and correct answers

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Total 147 Questions | Updated On: Feb 11, 2026

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Question 1

What is the purpose of dimensionality reduction in machine learning?

A : Data Augmentation

B : Model Evaluation

C : Model Regularization

D : Feature Extraction

E : Model Interpretation

F : Noise Reduction

Answer: D

Question 2

Which of the following is NOT a common technique for improving the performance of classification models?

A : Feature Engineering

B : Ensemble Learning

C : Hyperparameter Tuning

D : Regularization

E : Gradient Descent

F : Dimensionality Reduction

Answer: E

Question 3

What is the primary objective of k-means clustering?

A : Classification

B : Association Rule Learning

C : Regression

D : Dimensionality Reduction

E : Clustering

F : Anomaly Detection

Answer: E

Question 4

What is the primary objective of logistic regression in machine learning?

A : Unsupervised Learning

B : Classification

C : Clustering

D : Dimensionality Reduction

E : Regression

F : Anomaly Detection

Answer: B

Question 5

What is the primary objective of cross-entropy loss in classification tasks?

A : Maximize Prediction Accuracy

B : Minimize Prediction Error

C : Minimize Prediction Variance

D : Maximize Prediction Confidence

E : Measure Prediction Uncertainty

F : Improve Model Stability

Answer: C

Page: 1 / 30

Total 147 Questions | Updated On: Feb 11, 2026

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