MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist is using Amazon SageMaker to build a custom training algorithm. The algorithm requires a specific library that is not included in the default SageMaker containers. The scientist wants to create a custom container that includes this library. Which TWO steps are required? (Choose TWO.)
⚠ Common exam trap
The MLS-C01 exam often tests the misconception that Docker images can be stored in S3 for SageMaker, but the platform strictly requires ECR for container image storage and retrieval.
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
✓
Build a Docker image with the required library
Building a Docker image with the required library is the foundational step to create a custom container that includes dependencies not present in the default SageMaker containers. Option E is correct because the Docker image must be pushed to Amazon Elastic Container Registry (ECR) so that SageMaker can pull it when training jobs are launched. SageMaker does not directly use images stored in S3; it requires the image to be hosted in ECR.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Upload the Docker image to an Amazon S3 bucket
Why it's wrong here
Docker images are stored in ECR, not S3.
- ✗
Create an AWS Lambda layer with the library
Why it's wrong here
Lambda layers are for serverless functions, not for SageMaker training.
- ✓
Build a Docker image with the required library
Why this is correct
Docker is used to create custom containers.
- ✗
Register the container in the SageMaker Model Registry
Why it's wrong here
Model Registry is for model versions, not container images.
- ✓
Push the Docker image to Amazon ECR
Why this is correct
ECR is the registry for Docker images in AWS.
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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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.