- A
Enable active learning in Ground Truth to automatically select a subset of images for human labeling
Active learning iteratively selects the most valuable samples for human labeling, reducing cost while maintaining model performance.
- B
Label 100% of the images using a pre-built worker template to ensure accuracy
Why wrong: Labeling all images is unnecessary and expensive; active learning can achieve similar accuracy with fewer labels.
- C
Use Amazon SageMaker Data Wrangler to annotate images
Why wrong: Data Wrangler is for tabular and structured data preparation, not image annotation.
- D
Use automated labeling with a pre-trained model for all images and skip human review
Why wrong: Automated labeling may introduce errors, and without human verification, the quality may be insufficient for training.
MLA-C01 Practice Question: A data engineer is using Amazon SageMaker Ground…
This MLA-C01 practice question tests your understanding of mla-c01 exam topics. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data engineer is using Amazon SageMaker Ground Truth to create a labeled dataset for an object detection task. The dataset contains millions of images, and the labeling budget is limited. Which approach can reduce labeling costs while maintaining high model accuracy?
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 in Ground Truth to automatically select a subset of images for human labeling
Active learning in Ground Truth selects the most informative samples (e.g., uncertain predictions) for human labeling, reducing the number of labels needed while maximizing model improvement. This is a built-in feature.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 in Ground Truth to automatically select a subset of images for human labeling
Why this is correct
Active learning iteratively selects the most valuable samples for human labeling, reducing cost while maintaining model performance.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Label 100% of the images using a pre-built worker template to ensure accuracy
Why it's wrong here
Labeling all images is unnecessary and expensive; active learning can achieve similar accuracy with fewer labels.
- ✗
Use Amazon SageMaker Data Wrangler to annotate images
Why it's wrong here
Data Wrangler is for tabular and structured data preparation, not image annotation.
- ✗
Use automated labeling with a pre-trained model for all images and skip human review
Why it's wrong here
Automated labeling may introduce errors, and without human verification, the quality may be insufficient for training.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Similar concept trap
Labeling all images is unnecessary and expensive; active learning can achieve similar accuracy with fewer labels.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Enable active learning in Ground Truth to automatically select a subset of images for human labeling — Active learning in Ground Truth selects the most informative samples (e.g., uncertain predictions) for human labeling, reducing the number of labels needed while maximizing model improvement. This is a built-in feature.
What should I do if I get this MLA-C01 question wrong?
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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