MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
A team uses SageMaker Pipelines to train and evaluate a model. They want to run the training step only if the data quality check passes, otherwise skip. Which TWO pipeline step types are required? (Select TWO.)
⚠ Common exam trap
It's easy for candidates to think a Processing step (C) can handle conditional logic because it runs custom code, but SageMaker Pipelines requires a dedicated Condition step for branching; the Processing step is only for data processing, not for pipeline control flow.
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
✓
Condition step
The Condition step (B) is required because SageMaker Pipelines uses a Condition step to evaluate a boolean expression—such as whether a data quality check passed—and then conditionally execute subsequent steps. The Training step (D) is required because it is the step that actually runs the model training job, and it must be placed inside the 'If' branch of the Condition step to run only when the condition is true.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
RegisterModel step
Why it's wrong here
Registration is not needed for skipping training.
- ✓
Condition step
Why this is correct
Evaluates the condition and determines the next step.
- ✗
Processing step
Why it's wrong here
Processing could be used for data quality check, but the question asks for steps required for the conditional execution.
- ✓
Training step
Why this is correct
Executes the training if condition passes.
- ✗
Transform step
Why it's wrong here
Transform is for batch inference, not relevant.
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