- A
Steps in a pipeline must run sequentially.
Why wrong: They can run in parallel.
- B
Pipelines support caching of step outputs.
Caching speeds up re-runs.
- C
Pipelines can only use built-in algorithms.
Why wrong: Custom scripts are allowed.
- D
Pipelines cannot have conditional branches.
Why wrong: Conditional execution is supported.
Question 1,736 of 1,755
MLS-C01 Practice Question: Machine Learning Implementation and Operations
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. 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 machine learning engineer is building a pipeline using Amazon SageMaker Pipelines. The pipeline has multiple steps including data preprocessing, training, and evaluation. Which statement about SageMaker Pipelines is correct?
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
✓
Pipelines support caching of step outputs.
Option B is correct because SageMaker Pipelines supports output caching, which allows step outputs to be reused when the step configuration and inputs remain unchanged. This caching mechanism reduces execution time and cost by skipping redundant computations for steps like data preprocessing or training when their parameters have not changed.
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.
- ✗
Steps in a pipeline must run sequentially.
Why it's wrong here
They can run in parallel.
- ✓
Pipelines support caching of step outputs.
Why this is correct
Caching speeds up re-runs.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Pipelines can only use built-in algorithms.
Why it's wrong here
Custom scripts are allowed.
- ✗
Pipelines cannot have conditional branches.
Why it's wrong here
Conditional execution is supported.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume pipelines are strictly sequential (like traditional scripts) and overlook SageMaker's support for parallelism, custom code, and conditional logic, leading them to select option A or D.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Pipelines caching uses a hash of the step's input data, parameters, and image URI to determine cache hits; if the hash matches a previous execution, the cached output is used. This is particularly valuable in iterative development where preprocessing or training steps are repeated with minor changes, as it avoids re-running expensive operations. A real-world scenario is retraining a model only when new data arrives, while reusing cached feature engineering outputs from previous runs.
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.
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
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.
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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: Pipelines support caching of step outputs. — Option B is correct because SageMaker Pipelines supports output caching, which allows step outputs to be reused when the step configuration and inputs remain unchanged. This caching mechanism reduces execution time and cost by skipping redundant computations for steps like data preprocessing or training when their parameters have not changed.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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