AI0-001 AI Concepts and Foundations Practice Question
In the AI lifecycle, which phase involves splitting data into training, validation, and test sets?
⚠ Common exam trap
CompTIA often tests the misconception that data splitting belongs to model training or evaluation, when in fact it is a preprocessing step that must occur before any model sees the data.
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
✓
Data preprocessing
Data preprocessing is the phase where raw data is cleaned, transformed, and prepared for modeling. Splitting the dataset into training, validation, and test sets is a critical step during this phase to ensure unbiased evaluation and prevent data leakage. This split occurs before any model training begins, making it part of preprocessing rather than training or evaluation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Model training
Why it's wrong here
Incorrect; training uses the already-split training data.
- ✓
Data preprocessing
Why this is correct
Correct; preprocessing includes cleaning, transforming, and splitting data.
- ✗
Data collection
Why it's wrong here
Incorrect; data collection acquires raw data, not splitting.
- ✗
Model evaluation
Why it's wrong here
Incorrect; evaluation uses test data, but splitting happens earlier.
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Written by Johnson Ajibi, MSc IT Security
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