The answer is to create a model in SageMaker with the inference code, create an endpoint configuration with a production variant specifying instance type and initial variant weight, and then create the endpoint using that configuration. These three steps are necessary because SageMaker real-time endpoint setup requires first packaging the trained model artifact with an inference script into a Model object, then defining a production variant within an endpoint configuration that explicitly selects a GPU instance type (like ml.p3.2xlarge) and sets the initial traffic weight, and finally deploying that configuration to create the live endpoint. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of the deployment workflow versus training—a common trap is assuming you must retrain the model or configure auto-scaling as a prerequisite step, but neither is required for initial endpoint creation. A helpful memory tip is to think of the three C’s: Create the Model, Configure the variant, and Create the endpoint.
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 company is deploying a machine learning model on SageMaker for real-time inference. The model requires GPU for low latency. Which THREE steps are necessary to set up the endpoint?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a SageMaker model object that points to the S3 bucket containing the model artifacts and the inference container image
Correct options: A (Create a model in SageMaker with the inference code), C (Create an endpoint configuration with a production variant specifying instance type and initial variant weight), and D (Create an endpoint using the endpoint configuration). B is not necessary because the model is already trained. E is not necessary for real-time inference.
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.
✗
Train the model using a SageMaker training job
Why it's wrong here
The model is already trained.
✗
Create a SageMaker batch transform job
Why it's wrong here
Batch transform is for offline, not real-time.
✓
Create a SageMaker model object that points to the S3 bucket containing the model artifacts and the inference container image
Why this is correct
A model object is required to deploy an endpoint.
Related concept
Read the scenario before looking for a memorised answer.
✓
Create an endpoint configuration specifying the instance type (e.g., ml.p3.2xlarge) and initial instance count
Why this is correct
Endpoint configuration defines the infrastructure for the endpoint.
Related concept
Read the scenario before looking for a memorised answer.
✓
Create a SageMaker endpoint using the endpoint configuration
Why this is correct
The endpoint is created from the configuration.
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.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a SageMaker model object that points to the S3 bucket containing the model artifacts and the inference container image — Correct options: A (Create a model in SageMaker with the inference code), C (Create an endpoint configuration with a production variant specifying instance type and initial variant weight), and D (Create an endpoint using the endpoint configuration). B is not necessary because the model is already trained. E is not necessary for real-time inference.
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.
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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
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