MLA-C01 ML Model Development Practice Question
A team wants to use a custom PyTorch training script in SageMaker. They need to install additional Python packages not included in the base PyTorch container. Which approach should they take?
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 the SageMaker PyTorch estimator with a requirements.txt file
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 Script Mode with a custom Dockerfile
Why it's wrong here
Script mode still uses the built-in container; a custom container is not needed.
- ✗
Build a custom container with Docker
Why it's wrong here
This is possible but overkill; the built-in estimator supports requirements.txt.
- ✗
Install packages using a lifecycle configuration
Why it's wrong here
Lifecycle configs are for notebook instances, not training jobs.
- ✓
Use the SageMaker PyTorch estimator with a requirements.txt file
Why this is correct
The PyTorch estimator automatically installs packages from requirements.txt.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.