- A
Step 1: Enable data capture on the endpoint. Step 2: Create a baseline from training data. Step 3: Schedule the monitoring job. Step 4: Review the monitoring reports.
Correct order: Enable data capture to start collecting inference data, then create a baseline from training data, schedule the monitoring job, and finally review reports.
- B
Step 1: Create a baseline from training data. Step 2: Enable data capture on the endpoint. Step 3: Schedule the monitoring job. Step 4: Review the monitoring reports.
Why wrong: Incorrect: Creating a baseline before enabling data capture would leave no live data to compare against. Data capture must be enabled first to accumulate data for monitoring.
- C
Step 1: Enable data capture on the endpoint. Step 2: Schedule the monitoring job. Step 3: Create a baseline from training data. Step 4: Review the monitoring reports.
Why wrong: Incorrect: Scheduling the monitoring job before creating the baseline fails because the baseline is required for drift detection. Also, baseline comes after data capture.
- D
Step 1: Create a baseline from training data. Step 2: Schedule the monitoring job. Step 3: Enable data capture on the endpoint. Step 4: Review the monitoring reports.
Why wrong: Incorrect: Scheduling before enabling capture means no data to monitor, and baseline before capture is unnecessary without live data.
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.
Drag and drop the steps to evaluate a trained model using SageMaker Model Monitor in the correct order.
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
Step 1: Enable data capture on the endpoint. Step 2: Create a baseline from training data. Step 3: Schedule the monitoring job. Step 4: Review the monitoring reports.
Model Monitor requires enabling data capture, creating baseline, schedule, and reviewing reports.
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.
- ✓
Step 1: Enable data capture on the endpoint. Step 2: Create a baseline from training data. Step 3: Schedule the monitoring job. Step 4: Review the monitoring reports.
Why this is correct
Correct order: Enable data capture to start collecting inference data, then create a baseline from training data, schedule the monitoring job, and finally review reports.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Step 1: Create a baseline from training data. Step 2: Enable data capture on the endpoint. Step 3: Schedule the monitoring job. Step 4: Review the monitoring reports.
Why it's wrong here
Incorrect: Creating a baseline before enabling data capture would leave no live data to compare against. Data capture must be enabled first to accumulate data for monitoring.
- ✗
Step 1: Enable data capture on the endpoint. Step 2: Schedule the monitoring job. Step 3: Create a baseline from training data. Step 4: Review the monitoring reports.
Why it's wrong here
Incorrect: Scheduling the monitoring job before creating the baseline fails because the baseline is required for drift detection. Also, baseline comes after data capture.
- ✗
Step 1: Create a baseline from training data. Step 2: Schedule the monitoring job. Step 3: Enable data capture on the endpoint. Step 4: Review the monitoring reports.
Why it's wrong here
Incorrect: Scheduling before enabling capture means no data to monitor, and baseline before capture is unnecessary without live data.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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 — study guide chapter
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
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: Step 1: Enable data capture on the endpoint. Step 2: Create a baseline from training data. Step 3: Schedule the monitoring job. Step 4: Review the monitoring reports. — Model Monitor requires enabling data capture, creating baseline, schedule, and reviewing reports.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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.
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