AI0-001 AI Concepts and Techniques Practice Question
A data scientist is building a recommendation system for an e-commerce platform. The dataset includes user purchase history, product descriptions, and user demographics. The goal is to recommend products that a user is likely to purchase. Which TWO techniques are most appropriate for this task? (Select TWO.)
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
✓
Content-based filtering
Collaborative filtering uses user-item interactions; content-based filtering uses item features. Association rule mining is for basket analysis; regression is not typically used for recommendations; anomaly detection is for outliers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Content-based filtering
Why this is correct
Uses product descriptions and demographics to match user preferences.
- ✗
Association rule mining
Why it's wrong here
Typically used for market basket analysis, not personalized recommendations.
- ✗
Linear regression
Why it's wrong here
Predicts continuous values, not suitable for recommendation.
- ✗
Anomaly detection
Why it's wrong here
Detects outliers, not for recommendations.
- ✓
Collaborative filtering
Why this is correct
Leverages user purchase history to find similar users.
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JA
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.