AWSCertified Machine Learning Engineer - Associate
Domain 1Objective 2
Task 1.2: Transform Data and Perform Feature Engineering MLA-C01 Practice Questions (Page 4)
Part of the Content Domain 1: Data Preparation for Machine Learning (ML) domain, which accounts for 28% of the MLA-C01 exam. AWS does not publish an official question count, but from its 130-minute exam (~50–85 total, ~14–24 in this domain), expect 5–8 from this objective — we provide 25 practice questions to prepare you well beyond it. (estimate)
25questions here
5free pages
9concepts
28%of the exam
Questions 16–20
- 16
A company needs to create a labeled dataset for a text classification task and wants to use a combination of automated labeling and human review. Which AWS service provides a workflow that supports both automated and human labeling?
Select an answer first - 17
A data engineer needs to run a large-scale data transformation using Apache Spark on a managed cluster. Which AWS service is designed for this purpose?
Select an answer first - 18
A machine learning team wants to create a centralized repository where different models can access the same set of features. Which AWS service is designed for storing, managing, and sharing ML features?
Select an answer first - 19
A company wants to use a crowdsourcing platform to have a large number of independent workers label a dataset. Which AWS service provides access to a crowdsourced workforce for labeling tasks?
Select an answer first - 20
A data analyst wants to clean and normalize data using a visual, no-code interface with over 250 built-in transformations. Which AWS service is designed for this?
Select an answer first
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