- A
Use SageMaker Training steps with checkpointing
Why wrong: Checkpointing is for resuming training jobs, not for caching preprocessing outputs.
- B
Use SageMaker Processing steps with caching
Caching in SageMaker Pipelines reuses step outputs when inputs are identical, avoiding redundant computation.
- C
Use SageMaker Feature Store to store the preprocessed features
Why wrong: Feature Store is for online feature serving, not for caching intermediate pipeline step outputs.
- D
Use SageMaker Data Wrangler for the preprocessing
Why wrong: Data Wrangler creates preprocessing flows but caching is handled by Pipelines, not Data Wrangler itself.
MLA-C01 ML Model Development Practice Question
This MLA-C01 practice question tests your understanding of ml model development. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 science team is using Amazon SageMaker Pipelines to orchestrate a multi-step workflow that includes data preprocessing, training, and model evaluation. They want to reuse the preprocessed data across multiple pipeline executions without re-running the preprocessing step if the source data hasn't changed. What should they configure?
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
Use SageMaker Processing steps with caching
SageMaker Pipelines supports step caching, which allows reusing the output of a step if its inputs and parameters are unchanged. SageMaker Feature Store is for feature storage and serving, not for pipeline step reuse. Checkpointing is for training resumption, not step caching. Data Wrangler preprocesses but caching is a pipeline 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.
- ✗
Use SageMaker Training steps with checkpointing
Why it's wrong here
Checkpointing is for resuming training jobs, not for caching preprocessing outputs.
- ✓
Use SageMaker Processing steps with caching
Why this is correct
Caching in SageMaker Pipelines reuses step outputs when inputs are identical, avoiding redundant computation.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use SageMaker Feature Store to store the preprocessed features
Why it's wrong here
Feature Store is for online feature serving, not for caching intermediate pipeline step outputs.
- ✗
Use SageMaker Data Wrangler for the preprocessing
Why it's wrong here
Data Wrangler creates preprocessing flows but caching is handled by Pipelines, not Data Wrangler itself.
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
Checkpointing is for resuming training jobs, not for caching preprocessing outputs.
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 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?
ML Model Development — This question tests ML Model Development — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use SageMaker Processing steps with caching — SageMaker Pipelines supports step caching, which allows reusing the output of a step if its inputs and parameters are unchanged. SageMaker Feature Store is for feature storage and serving, not for pipeline step reuse. Checkpointing is for training resumption, not step caching. Data Wrangler preprocesses but caching is a pipeline 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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jun 23, 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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