MLS-C01 Exploratory Data Analysis Practice Question
Which THREE techniques are commonly used for feature engineering in exploratory data analysis? (Select THREE.)
⚠ Common exam trap
The MLS-C01 exam often tests the distinction between feature engineering (creating new features from existing data) and dimensionality reduction (PCA) or encoding (one-hot encoding), leading candidates to mistakenly select PCA as a feature engineering technique when it is actually a preprocessing step for reducing feature space.
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
✓
Extracting date/time components like day of week or hour.
Extracting date/time components such as day of week, hour, or month from a timestamp is a standard feature engineering technique. It transforms a single datetime column into multiple categorical or cyclical features that can reveal temporal patterns like weekly seasonality or peak hours, which are often critical for time-series models.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Extracting date/time components like day of week or hour.
Why this is correct
Temporal features often reveal patterns.
- ✗
Using principal component analysis (PCA) to create new features.
Why it's wrong here
PCA reduces dimensionality, but is not typically considered feature engineering; it transforms features.
- ✗
Applying one-hot encoding to numerical features.
Why it's wrong here
One-hot encoding is for categorical features.
- ✓
Creating interaction features between variables.
Why this is correct
Interaction features capture combined effects.
- ✓
Binning continuous variables into discrete intervals.
Why this is correct
Binning can capture non-linear relationships.
Go deeper
Related to this question
About these practice questions
One of 1,672 original MLS-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.