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AI0-001 AI Concepts and Foundations Practice Question

Which TWO of the following are appropriate uses of unsupervised learning?

⚠ Common exam trap

CompTIA often tests the distinction between supervised and unsupervised learning by presenting tasks that seem 'automatic' but actually require labeled data, tricking candidates into choosing supervised tasks as unsupervised uses.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Detecting unusual patterns in network traffic that may indicate a cyberattack

Unsupervised learning discovers hidden patterns or structures in unlabeled data. Detecting unusual patterns in network traffic (option C) is a classic anomaly detection task, often performed using clustering or autoencoders, where the model learns 'normal' behavior and flags deviations without requiring labeled attack data.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Classifying emails as spam or not spam

    Why it's wrong here

    This is supervised classification.

  • Predicting the sale price of a house given its features

    Why it's wrong here

    This is supervised regression.

  • Detecting unusual patterns in network traffic that may indicate a cyberattack

    Why this is correct

    Anomaly detection often uses unsupervised methods.

  • Identifying a person from a photo

    Why it's wrong here

    Facial recognition is typically supervised.

  • Segmenting customers into groups based on purchasing behavior

    Why this is correct

    Clustering is unsupervised.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.