Free Amazon MLA-C01 Exam Questions
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Amazon MLA-C01 Exam Questions
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Provided By: Amazon
- Exam: AWS Certified Machine Learning Engineer Associate
- Certification: AWS Certified Machine Learning
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Total Questions: 454
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Updated On: May 22, 2026
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Rated: 4.9 |
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Online Users: 908
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Question 1
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A company is building a near real-time data analytics application to detect anomalies and failures forindustrial equipment. The company has thousands of IoT sensors that send data every 60 seconds.When new versions of the application are released, the company wants to ensure that applicationcode bugs do not prevent the application from running.Which solution will meet these requirements?
Answer: A
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A company is building a near real-time data analytics application to detect anomalies and failures forindustrial equipment. The company has thousands of IoT sensors that send data every 60 seconds.When new versions of the application are released, the company wants to ensure that applicationcode bugs do not prevent the application from running.Which solution will meet these requirements?
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Question 2
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A Machine Learning Specialist is implementing a full Bayesian network on a dataset that describes public transit in New York City.One of the random variables is discrete and represents the number of minutes New Yorkers wait for a bus given that the buses cycle every 10 minutes, with a mean of 3 minutes.Which prior probability distribution should the ML Specialist use for this variable?
Answer: D
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A Machine Learning Specialist is implementing a full Bayesian network on a dataset that describes public transit in New York City.One of the random variables is discrete and represents the number of minutes New Yorkers wait for a bus given that the buses cycle every 10 minutes, with a mean of 3 minutes.Which prior probability distribution should the ML Specialist use for this variable?
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Question 3
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An ML engineer has developed a binary classification model outside of Amazon SageMaker. The ML
engineer needs to make the model accessible to a SageMaker Canvas user for additional tuning.
The model artifacts are stored in an Amazon S3 bucket. The ML engineer and the Canvas user are
part of the same SageMaker domain.
Which combination of requirements must be met so that the ML engineer can share the model with
the Canvas user? (Choose two.)
Answer: B,C
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An ML engineer has developed a binary classification model outside of Amazon SageMaker. The ML
engineer needs to make the model accessible to a SageMaker Canvas user for additional tuning.
The model artifacts are stored in an Amazon S3 bucket. The ML engineer and the Canvas user are
part of the same SageMaker domain.
Which combination of requirements must be met so that the ML engineer can share the model with
the Canvas user? (Choose two.)
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Question 4
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A travel company has trained hundreds of geographic data models to answer customer questions byusing Amazon SageMaker AI. Each model uses its own inferencing endpoint, which has become anoperational challenge for the company.The company wants to consolidate the models' inferencing endpoints to reduce operationaloverhead.Which solution will meet these requirements?
Answer: A
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A travel company has trained hundreds of geographic data models to answer customer questions byusing Amazon SageMaker AI. Each model uses its own inferencing endpoint, which has become anoperational challenge for the company.The company wants to consolidate the models' inferencing endpoints to reduce operationaloverhead.Which solution will meet these requirements?
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Question 5
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A company's ML engineer has deployed an ML model for sentiment analysis to an AmazonSageMaker AI endpoint. The ML engineer needs to explain to company stakeholders how the modelmakes predictions.Which solution will provide an explanation for the model's predictions?
Answer: B
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A company's ML engineer has deployed an ML model for sentiment analysis to an AmazonSageMaker AI endpoint. The ML engineer needs to explain to company stakeholders how the modelmakes predictions.Which solution will provide an explanation for the model's predictions?