MLA-C01 ML Model Development Practice Question
A company is training a deep learning model for object detection using SageMaker. The training is very slow and the GPU memory is insufficient for the batch size. The team wants to scale across multiple GPUs efficiently. Which THREE actions should they take? (Choose THREE.)
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 distributed model parallelism
Distributed data parallelism replicates the model and splits batches across GPUs. SageMaker distributed library optimizes this. Model parallelism splits the model when memory is insufficient. Spot instances reduce cost but not speed or memory. Debugger does not speed up training.
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 distributed model parallelism
Why this is correct
Model parallelism partitions the model across GPUs if the model is too large for one GPU.
- ✓
Use SageMaker distributed data parallelism
Why this is correct
Data parallelism splits the batch across GPUs, allowing larger effective batch sizes and faster training.
- ✗
Use managed spot instances
Why it's wrong here
Spot instances save cost but do not improve training speed or memory.
- ✓
Use a SageMaker distributed training configuration with the SageMaker SDK
Why this is correct
The SDK provides easy configuration for distributed training strategies.
- ✗
Enable SageMaker Debugger to identify bottlenecks
Why it's wrong here
Debugger helps debug but does not directly improve speed or memory.
Go deeper
Related to this question
About these practice questions
Courseiva writes every MLA-C01 question from scratch — 835 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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.