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

Q421

Which AWS service is used for real-time data processing?

A Amazon Kinesis
B Amazon S3
C AWS Lambda
D Amazon RDS

Explanation Amazon Kinesis is designed specifically for real-time data processing, unlike the others which serve different purposes.

Q422

A company needs to deploy a machine learning model with zero downtime. Which AWS service should they use?

A Amazon SageMaker
B AWS Batch
C AWS Elastic Beanstalk
D AWS CloudFormation

Explanation Amazon SageMaker offers model hosting with zero downtime capabilities for deployments, which the others do not guarantee.

Q423

What happens when you increase the instance size in an AWS EC2 Auto Scaling Group?

A More instances are launched immediately
B Current instances are terminated
C Existing instances are resized statically
D New configuration is only applied during scaling

Explanation The new instance size only applies when new instances are launched; existing instances remain unchanged until they are replaced during scaling events.

Q424

Which service is optimal for real-time stream data analysis?

A AWS Kinesis
B AWS S3
C AWS Lambda
D AWS SES

Explanation AWS Kinesis is designed for real-time streaming, while S3 is for storage, Lambda is for serverless compute, and SES is for email service.

Q425

A company needs to train a model on a large dataset that cannot fit in memory. Which AWS service/module should they use?

A SageMaker Batch Transform
B SageMaker Debugger
C SageMaker Ground Truth
D SageMaker Hyperparameter Tuning

Explanation SageMaker Batch Transform allows processing large datasets without fitting everything in memory; Debugger is for monitoring, Ground Truth is for data labeling, Hyperparameter Tuning optimizes model parameters.

Q426

You are configuring an IAM role for an EC2 instance running a machine learning model. What happens if you attach a restrictive policy?

A Access is granted to all resources.
B Access may be denied to resources.
C The instance will stop functioning.
D Only public resources can be accessed.

Explanation A restrictive IAM policy can deny access to the required AWS resources for your ML model, which may prevent it from functioning correctly; option A is incorrect as it describes the opposite scenario, C is incorrect since the instance remains functional, and D is misleading as public access won’t matter with restricted permissions.

Q427

Which service automatically scales your ML model deployments?

A Amazon SageMaker
B Amazon RDS
C AWS Lambda
D Amazon EC2

Explanation Amazon SageMaker offers automated scaling for model endpoints; RDS, Lambda, and EC2 do not specifically address ML model scaling.

Q428

A company needs to preprocess data for a deep learning model and wants to stay within AWS. Which service should they choose?

A AWS Glue
B Amazon S3
C AWS Batch
D Amazon EMR

Explanation AWS Glue is an ETL service tailored for data preprocessing; S3 is for storage, Batch manages batch jobs, and EMR runs big data processing frameworks.

Q429

You are configuring model training on SageMaker. What happens if you set a too high max runtime?

A Increased cost due to longer training
B Model will be trained faster
C Training will fail if exceeded
D Runtime will be ignored

Explanation Setting a high max runtime can lead to higher costs as training consumes more resources; it does not directly speed up or fail the training optimally.

Q430

Which service is best for real-time streaming analytics?

A Amazon Kinesis
B AWS Lambda
C Amazon S3
D Amazon EBS

Explanation Amazon Kinesis is designed for processing real-time streams, while the others serve different purposes.