- A
AWS Glue
Why wrong: Glue is for ETL, not model training.
- B
AWS Lambda
Why wrong: Lambda has resource limits unsuitable for distributed training.
- C
Amazon Redshift
Why wrong: Redshift is a data warehouse, not for training.
- D
Amazon EMR
EMR with Spark MLlib can perform distributed training.
- E
Amazon SageMaker
SageMaker offers distributed training libraries and model parallelism.
Question 573 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. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 scientist needs to select a model training infrastructure that supports distributed training across multiple GPUs and provides automatic model parallelism. Which TWO AWS services should the scientist consider?
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
✓
Amazon EMR
Amazon EMR is correct because it supports distributed training across multiple GPUs using frameworks like TensorFlow, PyTorch, and Apache Spark, and it can automatically handle model parallelism through its integration with Horovod or custom distributed training scripts. Amazon SageMaker is correct because it provides built-in distributed training libraries (e.g., SageMaker Distributed Data Parallel and Model Parallel) that automatically partition model layers across multiple GPUs, enabling efficient training of large models.
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.
- ✗
AWS Glue
Why it's wrong here
Glue is for ETL, not model training.
- ✗
AWS Lambda
Why it's wrong here
Lambda has resource limits unsuitable for distributed training.
- ✗
Amazon Redshift
Why it's wrong here
Redshift is a data warehouse, not for training.
- ✓
Amazon EMR
Why this is correct
EMR with Spark MLlib can perform distributed training.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Amazon SageMaker
Why this is correct
SageMaker offers distributed training libraries and model parallelism.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse data processing services (Glue, Redshift) or serverless compute (Lambda) with GPU-accelerated training infrastructure, overlooking that only services explicitly supporting distributed GPU training and model parallelism (SageMaker and EMR) are correct.
Detailed technical explanation
How to think about this question
Amazon SageMaker's Model Parallelism library uses a technique called 'pipeline parallelism' to split model layers across GPUs, reducing memory footprint and enabling training of models with billions of parameters. Amazon EMR leverages Apache Spark's distributed computing model with GPU-aware scheduling (e.g., via Spark-RAPIDS) to parallelize training across multiple instances, and it supports Horovod for all-reduce gradient synchronization. In practice, a data scientist might use SageMaker for managed training with automatic model sharding, while EMR is preferred when training is part of a larger Spark-based data pipeline.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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: Amazon EMR — Amazon EMR is correct because it supports distributed training across multiple GPUs using frameworks like TensorFlow, PyTorch, and Apache Spark, and it can automatically handle model parallelism through its integration with Horovod or custom distributed training scripts. Amazon SageMaker is correct because it provides built-in distributed training libraries (e.g., SageMaker Distributed Data Parallel and Model Parallel) that automatically partition model layers across multiple GPUs, enabling efficient training of large models.
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
This MLS-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 MLS-C01 exam.
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