Microsoft Azure AI Fundamentals Artificial Intelligence 2

Question 1

Which type of AI system learns from labeled training data to predict outcomes for new, unseen data?

Accepted Answer

Supervised learning

Answer

Supervised learning uses labeled input-output pairs so the model can learn to predict outputs for new inputs.

Question 2

A company wants to group customers into segments based on purchasing behavior without predefined categories. Which AI approach is most appropriate?

Accepted Answer

Unsupervised clustering

Answer

Unsupervised clustering identifies natural groupings in data without requiring labeled examples or predefined categories.

Question 3

What is the primary purpose of a validation dataset in machine learning model training?

Accepted Answer

To tune hyperparameters and detect overfitting during training

Answer

A validation dataset is held out during training to tune hyperparameters and monitor for overfitting before final evaluation.

Question 4

Which term describes a model that performs well on training data but poorly on new, unseen data?

Accepted Answer

Overfitting

Answer

Overfitting occurs when a model memorizes training data patterns rather than learning generalizable rules.

Question 5

In the context of responsible AI, what does the principle of 'reliability and safety' primarily address?

Accepted Answer

Ensuring AI systems produce consistent, accurate results and perform safely across conditions

Answer

Reliability and safety means AI systems should behave consistently, handle edge cases safely, and meet the needs they were designed for.

Microsoft Azure AI Fundamentals Practice Test