AWSCertified Machine Learning Engineer - Associate
Domain 3Objective 1
Task 3.1: Select Deployment Infrastructure Based on Existing Architecture and Requirements MLA-C01 Practice Questions (Page 2)
Part of the Content Domain 3: Deployment and Orchestration of ML Workflows domain, which accounts for 22% of the MLA-C01 exam. AWS does not publish an official question count, but from its 130-minute exam (~50–85 total, ~11–19 in this domain), expect 4–6 from this objective — we provide 33 practice questions to prepare you well beyond it. (estimate)
33questions here
7free pages
13concepts
22%of the exam
Questions 6–10
- 6
A team wants to deploy a trained model to a resource-constrained edge device, such as a Raspberry Pi. Which SageMaker feature can optimize the model to run efficiently on this device?
Select an answer first - 7
A company wants to deploy a model as a serverless function that can be invoked by other AWS services without managing any infrastructure. Which deployment target is most appropriate?
Select an answer first - 8
A company needs to deploy a machine learning model that was trained using a custom framework not natively supported by SageMaker's built-in algorithms. Which SageMaker feature allows the deployment of such a model?
Select an answer first - 9
A team has a model that requires a specific library version not included in SageMaker's provided containers. Which container option should they use?
Select an answer first - 10
A financial services company needs to generate credit risk scores for millions of customers in a nightly batch job. Which inference method is most appropriate for this workload?
Select an answer first
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