AI0-001 AI Concepts and Foundations Practice Question
A data scientist is preparing a dataset for supervised learning. Which TWO steps are essential?
⚠ Common exam trap
CompTIA often tests the distinction between mandatory preprocessing steps and optional optimizations, trapping candidates who confuse best practices (like normalization or outlier removal) with absolute requirements for supervised learning.
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
✓
Labeling the data
Labeling the data is essential for supervised learning because the algorithm requires input-output pairs to learn a mapping function. Without labeled data, the model cannot be trained to predict outcomes, as supervised learning relies on ground-truth targets for error correction during training.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
One-hot encoding all features
Why it's wrong here
Incorrect; one-hot encoding is only for categorical features, and not all features require it.
- ✗
Normalizing features
Why it's wrong here
Incorrect; normalization is beneficial but not essential for all algorithms.
- ✓
Labeling the data
Why this is correct
Correct; supervised learning requires labeled examples.
- ✗
Removing outliers
Why it's wrong here
Incorrect; outlier removal is optional and depends on the problem.
- ✓
Splitting into training and test sets
Why this is correct
Correct; splitting is essential to avoid data leakage and evaluate generalization.
About these practice questions
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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.