The answer is to deploy the candidate with the highest objective metric value from the SageMaker Autopilot leaderboard. This is correct because Autopilot automatically tunes and ranks all candidate models based on the objective metric you specify—such as accuracy, F1, or AUC—and the leaderboard reflects the best-performing configuration according to that metric. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of Autopilot’s automated model selection workflow and the importance of trusting its optimization process rather than manually picking a model or deploying all candidates, which wastes resources and risks overfitting. A common trap is assuming you should deploy the model with the highest raw accuracy on the training data, but Autopilot already accounts for generalization through cross-validation and the chosen objective. Memory tip: “Leaderboard leads—trust the top metric, not your gut.”
MLS-C01 Practice Question: Machine Learning Implementation and Operations
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. 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 team is using Amazon SageMaker Autopilot to automatically build models. The dataset has 50 features and 1 million rows. After training, Autopilot generates multiple candidates. The team wants to deploy the model with the highest accuracy. What is the best practice to select and deploy the model?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Deploy the candidate with the highest objective metric value from the Autopilot leaderboard
SageMaker Autopilot's best candidate is determined by the objective metric. Option B is wrong because deploying all candidates wastes resources. Option C is wrong because the highest accuracy may not generalize; using the best objective metric is standard. Option D is wrong because manual selection is subjective.
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.
✗
Deploy all candidates behind a multi-model endpoint and route traffic based on request features
Why it's wrong here
Overly complex and not recommended.
✗
Select the model with the highest validation accuracy after performing additional hyperparameter tuning
Why it's wrong here
Autopilot already optimizes; extra tuning may overfit.
✗
Manually review each candidate's architecture and select the one with the simplest design
Why it's wrong here
Accuracy should be primary, not simplicity.
✓
Deploy the candidate with the highest objective metric value from the Autopilot leaderboard
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
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.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-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.
Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Deploy the candidate with the highest objective metric value from the Autopilot leaderboard — SageMaker Autopilot's best candidate is determined by the objective metric. Option B is wrong because deploying all candidates wastes resources. Option C is wrong because the highest accuracy may not generalize; using the best objective metric is standard. Option D is wrong because manual selection is subjective.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-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.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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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.
Question Discussion
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