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 81–90 of 486

Q81

What happens when you enable versioning for an S3 bucket?

  • A All objects are encrypted.
  • B Older versions are deleted.
  • C Multiple object versions can be stored.
  • D Access is restricted to the latest version.
Explanation Enabling versioning allows storage of multiple versions of the same object, while others are false statements.
Q82

Which AWS service is ideal for real-time analytics on streaming data?

  • A Amazon Kinesis
  • B Amazon S3
  • C Amazon RDS
  • D Amazon EC2
Explanation Amazon Kinesis is designed specifically for real-time data processing, unlike other services which are not tailored for streaming analytics.
Q83

A company needs a scalable machine learning model to serve predictions. What should they use?

  • A AWS Lambda
  • B Amazon SageMaker
  • C Amazon EC2
Explanation Amazon SageMaker is specifically designed to build and deploy scalable ML models, unlike the others which are more general purpose.
Q84

What happens when you increase the 'max_depth' parameter in a decision tree model?

  • A Model accuracy always increases
  • B Risk of overfitting increases
  • C Training time decreases
  • D Bias decreases significantly
Explanation Increasing 'max_depth' often leads to overfitting, which can reduce the model's generalization to unseen data.
Q85

Which service would you use for real-time data processing in AWS?

  • A Amazon Kinesis
  • B Amazon S3
  • C AWS Lambda
  • D AWS Glue
Explanation Amazon Kinesis is designed for real-time data processing, while S3 is for storage, Lambda can handle code execution, and Glue is mainly for ETL.
Q86

A company needs to deploy a machine learning model with minimal operational overhead. Which service should they choose?

  • A Amazon SageMaker
  • B Amazon EC2
  • C AWS Batch
  • D AWS Lambda
Explanation Amazon SageMaker simplifies model deployment, unlike EC2 and Lambda which require more setup.
Q87

You are configuring an AWS IAM policy. What happens if the policy denies access to a resource?

  • A Access is allowed conditionally.
  • B Access is completely denied.
  • C Access may be granted under certain conditions.
  • D The action is logged for review.
Explanation In IAM, a deny statement always takes precedence over allow statements.
Q88

Which service is best for real-time data analytics?

  • A Amazon Kinesis
  • B AWS Glue
  • C Amazon RDS
  • D AWS Batch
Explanation Amazon Kinesis supports real-time analytics; others are not designed for that specific purpose.
Q89

A company needs to identify the top 1% of customers based on spending. Which ML model type is most appropriate?

  • A Regression model
  • B Clustering model
  • C Classification model
  • D Anomaly detection model
Explanation A classification model can effectively categorize customers based on spending; regression is for continuous outputs, clustering for group similarity, and anomaly detection for rare events.
Q90

You are configuring an AWS SageMaker training job and select a dataset that has missing values. What should you do?

  • A Submit the job; SageMaker handles it.
  • B Perform data imputation beforehand.
  • C Ignore the missing values.
  • D Use a simpler model.
Explanation Performing data imputation is necessary to handle missing values effectively; SageMaker does not automatically fix them, and ignoring or simplifying won't provide accurate results.