AI Associate AI Fundamentals Practice Question
A company is deploying an AI model to automatically classify customer emails into categories (Complaint, Inquiry, Feedback). They have 10,000 labeled emails. Which TWO actions are essential to ensure the model's accuracy? (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
✓
Split the data into training and test sets
Splitting data into train/test sets allows evaluation of generalization. Ensuring balanced representation of categories prevents bias towards majority classes.
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 the model until it achieves 100% accuracy on the training set
Why it's wrong here
100% training accuracy indicates overfitting; the goal is generalization.
- ✓
Split the data into training and test sets
Why this is correct
Essential to evaluate model performance on unseen data.
- ✗
Use only the most recent 1,000 emails for training to reflect current trends
Why it's wrong here
Using only recent data may miss older patterns and reduce sample size unnecessarily.
- ✗
Remove all emails that contain spelling errors
Why it's wrong here
Spelling errors are common in real emails; removing them would create unrealistic training data.
- ✓
Ensure all three categories are adequately represented in the training data
Why this is correct
Essential to avoid a model that never predicts a rare category.
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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.