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 301–310 of 486

Q301

A company needs to deploy a machine learning model in production. Which AWS service should they use for real-time inference?

  • A Amazon SageMaker
  • B Amazon S3
  • C Amazon Redshift
  • D AWS Lambda
Explanation Amazon SageMaker provides a fully managed service for deploying machine learning models with real-time inference; S3 is for storage, Redshift for data warehousing, and Lambda for serverless computations.
Q302

What happens when you delete an Amazon S3 bucket that contains objects?

  • A Only the objects are deleted
  • B Bucket is deleted, objects are retained
  • C Bucket deletion fails
  • D Bucket and all objects are deleted
Explanation When you delete an S3 bucket, it deletes both the bucket and all its objects permanently; retention is not an option.
Q303

You are configuring IAM roles for a data scientist to train models using AWS SageMaker. What is a best practice?

  • A Grant admin access to all services
  • B Use least privilege access
  • C Attach the default role
  • D Allow unrestricted access to S3
Explanation Using least privilege access ensures the data scientist has only necessary permissions, enhancing security; other options pose excessive risk.
Q304

Which service is best for real-time data streaming?

  • A Amazon Kinesis
  • B Amazon S3
  • C Amazon RDS
  • D AWS Lambda
Explanation Amazon Kinesis is designed specifically for real-time data streaming, whereas the others serve different purposes.
Q305

A healthcare company wants to predict patient outcomes based on historical data. Which AWS service should they use?

  • A Amazon Comprehend
  • B AWS SageMaker
  • C Amazon QuickSight
  • D AWS Glue
Explanation AWS SageMaker is tailored for building, training, and deploying machine learning models.
Q306

What happens when you incorrectly configure IAM permissions for a SageMaker role?

  • A Job runs but outputs are empty
  • B Job fails and returns an error
  • C Permissions are ignored completely
  • D Job runs with reduced performance
Explanation Incorrect IAM permissions will lead to job failures, as required access is not granted.
Q307

Which service is ideal for deploying machine learning models at scale?

  • A Amazon SageMaker
  • B AWS Glue
  • C Amazon RDS
  • D Amazon EC2
Explanation Amazon SageMaker is specifically built for deploying ML models, while others serve different purposes.
Q308

A company needs to process streaming data in real-time for its fraud detection system. Which AWS service should they use?

  • A Amazon S3
  • B Amazon Kinesis
  • C AWS Lambda
  • D AWS Batch
Explanation Amazon Kinesis is designed for real-time streaming data, unlike the others which serve different use cases.
Q309

You are configuring an IAM policy that denies all actions for a specific S3 bucket. What will happen if you grant another policy that allows access to that bucket?

  • A Access is granted due to explicit allow.
  • B Access is denied due to explicit deny.
  • C An error occurs during policy evaluation.
  • D Access is granted temporarily.
Explanation By default, explicit denies take precedence over allows in IAM policy evaluation.
Q310

Which service is best for deploying machine learning models at scale?

  • A AWS Lambda
  • B Amazon SageMaker
  • C AWS EC2
  • D AWS Glue
Explanation Amazon SageMaker is specifically designed for ML model deployment, unlike others which serve different purposes.