AI Associate AI Fundamentals Practice Question
An e-commerce company uses AI to provide product recommendations. The model suggests popular items but fails to personalize for individual users. Which type of learning could improve personalization?
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
✓
Supervised learning
Supervised learning can use user purchase history as labels to predict what a specific user might buy, enabling personalization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Generative AI
Why it's wrong here
Generative AI creates new items, not personalized recommendations based on behavior.
- ✗
Unsupervised learning
Why it's wrong here
Unsupervised learning finds patterns but does not use user-specific labels for personalization.
- ✗
Reinforcement learning
Why it's wrong here
Reinforcement learning is for sequential decisions, not standard recommendation personalization.
- ✓
Supervised learning
Why this is correct
Supervised learning can train on user-item interactions to predict personalized recommendations.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.