MLS-C01 Modeling Practice Question
A data scientist is using Amazon SageMaker to train a deep learning model on a large dataset stored in S3. The training job is taking too long. The data scientist wants to reduce training time without changing the model architecture. Which action 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 Pipe mode for data input
Using Pipe mode streams training data directly from S3 without first downloading it to the instance's local storage, significantly reducing I/O time and therefore overall training time. Option A is correct. Option B is incorrect because using a smaller instance type reduces compute capacity, which would likely increase training time. Option C is incorrect because increasing the number of epochs would increase training time, not decrease it. Option D is incorrect because decreasing the batch size typically results in more gradient updates per epoch, which can increase training time.
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 Pipe mode for data input
Why this is correct
Pipe mode streams data, reducing download time.
- ✗
Use a smaller instance type
Why it's wrong here
Smaller instance has less compute power, increasing training time.
- ✗
Increase the number of epochs
Why it's wrong here
More epochs increase training time.
- ✗
Decrease the batch size
Why it's wrong here
Smaller batch size increases the number of iterations per epoch.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.