Amazon AWS

AWS Certified Machine Learning Engineer – Associate

MLA-C01

The AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam validates your skills in building, training, and deploying machine learning models on AWS. It is ideal for those looking to specialize in machine learning.

486 questions 0 views Free
Start Mock Test Timed · Full-length · Scored

Questions 101–110 of 486

Q101

A company needs to deploy a predictive maintenance model for factory equipment. Which ML strategy would be most suitable?

  • A Clustering
  • B Supervised Learning
  • C Reinforcement Learning
  • D Unsupervised Learning
Explanation Supervised Learning is best for predictive tasks based on labeled data.
Q102

You are configuring IAM roles for an EKS cluster. What happens if permissions are too permissive?

  • A Increased security risks
  • B EKS cluster will malfunction
  • C Costs will increase
  • D No impact on operations
Explanation Too permissive permissions expose resources to security threats, while others are incorrect consequences.
Q103

What service would you use for the automatic deployment of machine learning models?

  • A Amazon SageMaker
  • B AWS Glue
  • C Amazon Comprehend
  • D Amazon QuickSight
Explanation Amazon SageMaker is designed specifically for deploying ML models; others do not focus on model deployment.
Q104

A company needs to perform real-time inference on streaming data. Which service is best suited for this?

  • A Amazon S3
  • B Amazon Kinesis
  • C AWS Batch
  • D Amazon RDS
Explanation Amazon Kinesis is ideal for real-time data streaming; the others are not designed for real-time processing.
Q105

You are configuring an event-driven architecture with AWS. What happens when a Lambda function runs for more time than its timeout setting?

  • A Function continues running until complete
  • B Function is terminated and fails
  • C Function returns partially processed result
  • D Function retries automatically until success
Explanation The Lambda function will terminate and fail if it exceeds the timeout; others imply incorrect behavior.
Q106

Which AWS service is best for version control of machine learning models?

  • A S3 Versioning
  • B CodeCommit
  • C SageMaker Model Registry
  • D Lambda Layers
Explanation SageMaker Model Registry is designed specifically for managing ML model versions, while the others do not offer this specific functionality.
Q107

A company needs to deploy a scalable real-time prediction API. Which service should they use?

  • A AWS Batch
  • B SageMaker Hosting Services
  • C Elastic Map Reduce
  • D RDS Multi-AZ
Explanation SageMaker Hosting Services provide a scalable endpoint for real-time predictions, unlike the other options.
Q108

What happens when you use a model built with SageMaker in a Lambda function?

  • A Lambda can execute without memory constraints
  • B Invocation results in faster execution times
  • C There is no latency in model predictions
  • D You must manage resource scaling manually
Explanation Using Lambda with SageMaker requires managing resource scaling, as Lambda has its own execution environment limits.
Q109

Which AWS service can analyze unstructured data using machine learning?

  • A Amazon Comprehend
  • B Amazon S3
  • C Amazon EC2
  • D Amazon RDS
Explanation Amazon Comprehend specializes in natural language processing to analyze unstructured data, while the others do not focus on unstructured data analysis.
Q110

A company needs to manage data storage life cycles. Which S3 feature should they use?

  • A S3 Glacier
  • B S3 Lifecycle Policies
  • C S3 Versioning
  • D S3 Events
Explanation S3 Lifecycle Policies allow automatic management of data lifecycle, unlike Glacier, versioning, or events.