AWSCertified Machine Learning Engineer - Associate
Domain 3Objective 2
Task 3.2: Create and Script Infrastructure Based on Existing Architecture and Requirements MLA-C01 Practice Questions (Page 3)
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
11concepts
22%of the exam
Questions 11–15
- 11
Which AWS compute option is most cost-effective for running a fault-tolerant, interruptible ML training job?
Select an answer first - 12
Which AWS CDK construct is used to define a resource that can be referenced by other stacks?
Select an answer first - 13
Which metric is commonly used to configure target tracking scaling for a SageMaker AI endpoint?
Select an answer first - 14
A company runs a production ML inference service that requires consistent performance and cannot tolerate interruptions. They are considering using Spot Instances to reduce costs. Which approach should they take?
Select an answer first - 15
A company uses AWS CDK to define their ML infrastructure. They have a VPC stack and a SageMaker endpoint stack. The endpoint stack needs the VPC ID from the VPC stack. How should they pass this information?
Select an answer first
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