MLA-C01 Data Preparation for Machine Learning Practice Question
A data scientist is performing feature engineering for a dataset with both numerical and categorical features. The data scientist wants to apply transformations that preserve the interpretability of the features. Which TWO transformations should the data scientist use? (Select TWO)
⚠ Common exam trap
AWS often tests the misconception that one-hot encoding always preserves interpretability (it does, but the question pairs it with target encoding as a distractor), leading candidates to select one-hot encoding instead of recognizing that standard scaling is the correct second choice for numerical features.
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
✓
Log transformation of skewed numerical features
Log transformation is correct because it reduces skewness in numerical features by compressing the scale of large values, making the distribution more normal while preserving the original feature's interpretability (e.g., a log-transformed income value still relates to income). This is a monotonic transformation, so the order of values is maintained, and the feature remains directly understandable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Log transformation of skewed numerical features
Why this is correct
Log transformation reduces skewness while keeping feature order.
- ✗
Target encoding of high-cardinality categorical features
Why it's wrong here
Target encoding can cause data leakage and reduces interpretability.
- ✓
Standard scaling of numerical features
Why this is correct
Standard scaling is reversible and preserves feature relationships.
- ✗
PCA dimensionality reduction
Why it's wrong here
PCA transforms features into uninterpretable components.
- ✗
One-hot encoding of categorical features
Why it's wrong here
One-hot encoding adds many columns, complicating interpretability.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLA-C01 exam.