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: Mar 10, 2025

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Question 1

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

Question 2

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 3

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

Question 4

Which of these metrics is used to evaluate a classifier's performance?

A : Accuracy

B : Mean Squared ErrorCorrect selection

C : Precision

D : Recall

E : F1 Score

F : Root Mean Squared Error

Answer: A,C,D,E

Question 5

How does batch normalization help in training deep neural networks?

A : By reducing overfitting

B : By speeding up convergence

C : By increasing model accuracy

D : By simplifying the model architecture

Answer: B

Page: 1 / 30

Total 147 Questions | Updated On: Mar 10, 2025

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