MLS-C01 Modeling Practice Question
Which TWO of the following are best practices for training deep learning models on Amazon SageMaker? (Select TWO.)
⚠ Common exam trap
Many exam-takers confuse SageMaker Processing with a general-purpose compute environment for any training task, when in fact it is specifically for data processing jobs, not for augmenting data during model training.
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 input mode to stream data directly from S3 to the algorithm.
SageMaker's Pipe input mode streams training data directly from Amazon S3 to the algorithm without writing it to disk, reducing I/O latency and eliminating the need for large local storage. This is especially beneficial for deep learning models that iterate over large datasets, as it allows training to start faster and avoids the overhead of downloading data to EBS volumes.
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 Processing to perform data augmentation before training.
Why it's wrong here
Augmentation can be done on the fly during training.
- ✓
Use Pipe input mode to stream data directly from S3 to the algorithm.
Why this is correct
Pipe mode reduces startup time and storage.
- ✗
Store training data on Amazon EBS volumes attached to the training instance.
Why it's wrong here
Data should be in S3 for scalability.
- ✓
Use managed spot training to reduce costs.
Why this is correct
Spot instances can reduce training cost by up to 70%.
- ✗
Disable checkpointing to improve training speed.
Why it's wrong here
Checkpointing is important for recovery.
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 |
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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.