- A
Upload the Docker image to an Amazon S3 bucket
Why wrong: Docker images are stored in ECR, not S3.
- B
Create an AWS Lambda layer with the library
Why wrong: Lambda layers are for serverless functions, not for SageMaker training.
- C
Build a Docker image with the required library
Docker is used to create custom containers.
- D
Register the container in the SageMaker Model Registry
Why wrong: Model Registry is for model versions, not container images.
- E
Push the Docker image to Amazon ECR
ECR is the registry for Docker images in AWS.
Question 1,519 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. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 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.)
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
Option C is correct because 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.
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.
- ✗
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
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.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
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.
Detailed technical explanation
How to think about this question
When building a custom training container for SageMaker, you must extend or create a Docker image that implements the SageMaker Training Toolkit API, including the `/opt/ml/input/config` and `/opt/ml/model` directories. The image must be pushed to ECR using the `docker push` command with the appropriate repository URI (e.g., `aws_account_id.dkr.ecr.region.amazonaws.com/image:tag`). SageMaker then uses this ECR URI to pull the image onto the training instance, ensuring the custom library is available in the container's Python environment.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
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: Build a Docker image with the required library — Option C is correct because 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.
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.
About these practice questions
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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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