easyMultiple SelectObjective-mapped
MLA-C01 Practice Question: A data scientist is using Amazon SageMaker Data…
A data scientist is using Amazon SageMaker Data Wrangler to prepare a dataset. The dataset contains a column with missing values, a column with outliers, and a column with text data. The scientist wants to use built-in transforms to handle these issues. Which THREE transforms are available in Data Wrangler for these tasks? (Select THREE.)
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
✓
Handle missing values (imputation)
Data Wrangler provides built-in transforms for handling missing values (e.g., imputation), handling outliers (e.g., clipping), and processing text (e.g., tokenization). SMOTE is available for class imbalance, and one-hot encoding is for categorical features.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Handle missing values (imputation)
Why this is correct
Data Wrangler includes transforms to impute missing values using mean, median, etc.
- ✗
SMOTE oversampling
Why it's wrong here
SMOTE is not a built-in transform in Data Wrangler; it must be applied in a notebook or training script.
- ✗
One-hot encoding
Why it's wrong here
While one-hot encoding is available, the question specifically asks for transforms to handle missing values, outliers, and text, not categorical encoding.
- ✓
Handle outliers (clipping or Z-score)
Why this is correct
Data Wrangler has transforms to detect and handle outliers.
- ✓
Text processing (tokenization, TF-IDF)
Why this is correct
Data Wrangler includes text transforms like tokenization and TF-IDF.
Go deeper
Related to this question
About these practice questions
This MLA-C01 question is part of Courseiva's 835-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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.