AI Associate AI Fundamentals Practice Question
A company wants to generate personalized product recommendations for each customer based on their purchase history and browsing behavior. Which approach is MOST appropriate?
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
✓
Train a supervised learning model on historical purchase data to predict the next product a customer will buy
Supervised learning can predict what a customer might buy next based on labeled data (past purchases). Unsupervised learning can cluster customers but doesn't directly generate recommendations. Reinforcement learning is for dynamic environments, and generative AI creates content, not recommendations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Train a supervised learning model on historical purchase data to predict the next product a customer will buy
Why this is correct
Supervised learning can use features like past purchases and browsing to predict the next purchase for each customer.
- ✗
Use a generative AI model to create new product descriptions for each customer
Why it's wrong here
Generative AI creates content, not personalized recommendations based on behavior.
- ✗
Deploy a reinforcement learning agent that explores different recommendations in real-time
Why it's wrong here
Deploying a reinforcement learning agent is inappropriate here because initial product recommendations primarily involve supervised learning from existing purchase history and browsing data to predict user preferences. Real-time exploration risks negative customer experiences during the learning phase. This option is tempting as RL excels in optimising sequential decision-making in dynamic environments, such as game AI or optimising a series of interactions for long-term user engagement, where actions have delayed rewards.
- ✗
Use an unsupervised learning algorithm to cluster customers and recommend popular items in each cluster
Why it's wrong here
Clustering groups similar customers but doesn't personalize based on individual purchase history.
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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.