hardMultiple SelectObjective-mapped
MLA-C01 Practice Question: A team is using Amazon SageMaker Ground Truth to…
A team is using Amazon SageMaker Ground Truth to build a labeled dataset for a multi-class classification task. They have a small budget and want to reduce labeling costs. Which THREE features or strategies should they use? (Select THREE.)
⚠ Common exam trap
A common mix-up: candidates assume using a public workforce (Mechanical Turk) is always cheaper, but the question specifically asks for cost-reduction strategies, and a private workforce with domain expertise reduces rework and per-label costs, while active learning and pre-built workflows directly minimize the number of labels needed.
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
✓
Enable active learning to select the most informative samples
Active learning in SageMaker Ground Truth automatically selects the most informative or uncertain samples from the unlabeled dataset to be sent for human labeling. By focusing labeling effort on these high-value data points, the team can achieve a high-quality model with significantly fewer labeled examples, directly reducing labeling costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable active learning to select the most informative samples
Why this is correct
Active learning reduces the number of samples needed for labeling.
- ✓
Use a pre-built annotation workflow for image classification
Why this is correct
Pre-built workflows streamline the labeling process, reducing time and cost.
- ✓
Use a private workforce with domain expertise
Why this is correct
A private workforce may be more efficient and accurate, reducing overall cost for complex tasks.
- ✗
Use a public workforce (Mechanical Turk) for all labeling
Why it's wrong here
Public workforce may be cheaper per label but can be less accurate, leading to rework costs; not necessarily cost-saving.
- ✗
Label all data manually without automation
Why it's wrong here
Manual labeling without active learning or pre-built workflows is more expensive.
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.