- 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.
Quick Answer
The answer is to push the Docker image to Amazon ECR. This is correct because SageMaker training jobs can only pull container images from Amazon Elastic Container Registry (ECR), so after building your custom Docker image with the required library, you must push it to ECR and then reference that URI in the training job configuration. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this concept tests your understanding of the SageMaker training architecture, where custom containers are stored in ECR—not S3 or the Model Registry—and the exam often includes traps like confusing ECR with S3 for image storage or suggesting Lambda as a training runtime. A common memory tip is to think of ECR as the "garage" for your Docker images: you build the car (container), then park it in the garage (ECR) so SageMaker can drive it for training.
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 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
Options B and D are correct. The custom container must be built using Docker, and it must be pushed to Amazon ECR to be used by SageMaker. Option A is wrong because the container does not need to be registered in SageMaker Model Registry. Option C is wrong because the container image is stored in ECR, not S3. Option E is wrong because AWS Lambda is for serverless functions, not for running training containers.
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
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
- →
Machine Learning Implementation and Operations — study guide chapter
Learn the concepts, then practise the questions
- →
Machine Learning Implementation and Operations practice questions
Targeted practice on this topic area only
- →
All MLS-C01 questions
1,755 questions across all exam domains
- →
AWS Certified Machine Learning Specialty MLS-C01 study guide
Full concept coverage aligned to exam objectives
- →
MLS-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related MLS-C01 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Data Engineering practice questions
Practise MLS-C01 questions linked to Data Engineering.
Machine Learning Implementation and Operations practice questions
Practise MLS-C01 questions linked to Machine Learning Implementation and Operations.
Modeling practice questions
Practise MLS-C01 questions linked to Modeling.
Exploratory Data Analysis practice questions
Practise MLS-C01 questions linked to Exploratory Data Analysis.
MLS-C01 fundamentals practice questions
Practise MLS-C01 questions linked to MLS-C01 fundamentals.
MLS-C01 scenario practice questions
Practise MLS-C01 questions linked to MLS-C01 scenario.
MLS-C01 troubleshooting practice questions
Practise MLS-C01 questions linked to MLS-C01 troubleshooting.
Practice this exam
Start a free MLS-C01 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
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 — Options B and D are correct. The custom container must be built using Docker, and it must be pushed to Amazon ECR to be used by SageMaker. Option A is wrong because the container does not need to be registered in SageMaker Model Registry. Option C is wrong because the container image is stored in ECR, not S3. Option E is wrong because AWS Lambda is for serverless functions, not for running training containers.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More MLS-C01 practice questions
- A company is using Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda fu…
- A team is building a data pipeline to process terabytes of log data daily using Amazon EMR. The data arrives in 5-minute…
- A data science team is building a real-time fraud detection system. Transactions are streamed via Amazon Kinesis Data St…
- A company uses Amazon SageMaker to train and deploy machine learning models. The training data is stored in Amazon S3 (P…
- A data engineer is building a data pipeline to process user clickstream data. The data arrives as JSON files in an S3 bu…
- A data engineering team is designing a data lake on AWS for machine learning workloads. The data includes structured, se…
Last reviewed: Jun 20, 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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.