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: Dec 17, 2025

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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 these is a benefit of using convolutional neural networks (CNNs) for image processing?

A : They require smaller datasets

B : They are less computationally intensive

C : They automatically detect important features

D : They do not require labeled data

Answer: C

Question 3

In which phase of the machine learning process are hyperparameters tuned to optimize model performance?

A : Model Deployment

B : Model Evaluation

C : Model Training

D : Feature Engineering

E : Hyperparameter Tuning

F : Data Preprocessing

Answer: E

Question 4

What is the primary objective of semi-supervised learning in machine learning?

A : Eliminate Overfitting

B : Minimize Labeling Costs

C : Enhance Model Performance

D : Increase Model Transparency

E : Maximize Model Complexity

F : Reduce Training Time

Answer: B

Question 5

What is the purpose of the "learning rate" in gradient descent?

A : To control the speed of model training

B : To adjust the weight of input features

C : To determine the number of layers in a neural network

D : To set the threshold for classification

Answer: A

Page: 1 / 30

Total 147 Questions | Updated On: Dec 17, 2025

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