- A
Candidate definition notebook
Contains the generated code for data preprocessing and model training, showing the exact steps Autopilot applied.
- B
Model leaderboard
Why wrong: The model leaderboard only shows performance metrics, not preprocessing steps.
- C
Autopilot job description in AWS CloudTrail
Why wrong: The Autopilot job description in CloudTrail records API calls, not the preprocessing steps.
- D
Data exploration report
Includes statistics and visualizations as well as a summary of the preprocessing steps (e.g., imputation, scaling, encoding) that Autopilot performed, so it is a valid source.
- E
Explainability report
Why wrong: The explainability report shows feature importance, not preprocessing steps.
Question 67 of 1,000
SageMaker Autopilot Preprocessing Steps Location
This MLA-C01 practice question tests your understanding of ml model development. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. A key principle to apply: sageMaker Autopilot. 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 scientist is using SageMaker Autopilot for a regression problem. They want to see which data preprocessing steps Autopilot applied. Which TWO sources can they use to find this information?
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
✓
Candidate definition notebook
The two sources that show the data preprocessing steps applied by SageMaker Autopilot are the candidate definition notebook and the data exploration report. The candidate definition notebook contains the generated Python code for the entire pipeline, including all preprocessing transformations. The data exploration report provides a summary of the data and includes information about the transformations that were automatically applied. The model leaderboard only lists the performance metrics of the trials, not the preprocessing steps. The Autopilot job description in AWS CloudTrail logs the API calls made, but does not capture the preprocessing steps. The explainability report shows feature importance values, not the preprocessing steps.
Key principle: SageMaker Autopilot
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Candidate definition notebook
Why this is correct
Contains the generated code for data preprocessing and model training, showing the exact steps Autopilot applied.
Related concept
SageMaker Autopilot
- ✗
Model leaderboard
Why it's wrong here
The model leaderboard only shows performance metrics, not preprocessing steps.
- ✗
Autopilot job description in AWS CloudTrail
Why it's wrong here
The Autopilot job description in CloudTrail records API calls, not the preprocessing steps.
- ✓
Data exploration report
Why this is correct
Includes statistics and visualizations as well as a summary of the preprocessing steps (e.g., imputation, scaling, encoding) that Autopilot performed, so it is a valid source.
Related concept
SageMaker Autopilot
- ✗
Explainability report
Why it's wrong here
The explainability report shows feature importance, not preprocessing steps.
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
Command / output trap
The model leaderboard only shows performance metrics, not preprocessing steps.
Detailed technical explanation
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- SageMaker Autopilot
- Candidate definition notebook
- Data exploration report
TExam Day Tips
- 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
SageMaker Autopilot
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. SageMaker Autopilot 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.
Review sageMaker Autopilot, then practise related MLA-C01 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Model Development — This question tests ML Model Development — SageMaker Autopilot.
What is the correct answer to this question?
The correct answer is: Candidate definition notebook — The two sources that show the data preprocessing steps applied by SageMaker Autopilot are the candidate definition notebook and the data exploration report. The candidate definition notebook contains the generated Python code for the entire pipeline, including all preprocessing transformations. The data exploration report provides a summary of the data and includes information about the transformations that were automatically applied. The model leaderboard only lists the performance metrics of the trials, not the preprocessing steps. The Autopilot job description in AWS CloudTrail logs the API calls made, but does not capture the preprocessing steps. The explainability report shows feature importance values, not the preprocessing steps.
What should I do if I get this MLA-C01 question wrong?
Review sageMaker Autopilot, then practise related MLA-C01 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
SageMaker Autopilot
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Last reviewed: Jul 4, 2026
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