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.
Which AWS service is best for building and deploying machine learning models at scale?
ASageMaker
BEC2
CLambda
DRDS
Explanation
SageMaker is specifically designed for machine learning workflows, while others serve different purposes.
Q212
A company needs to preprocess their training data stored in S3. Which service should they use?
AAmazon EMR
BAWS Glue
CAmazon Athena
DDirect Connect
Explanation
AWS Glue provides ETL capabilities to preprocess data effectively, unlike the other options.
Q213
You are configuring an S3 bucket policy. What will happen if you set 'Block Public Access' to 'On'?
APublic access is allowed.
BAll objects are encrypted.
CPublic access is denied.
DOnly admin can access.
Explanation
Setting 'Block Public Access' to 'On' denies all public access, which is crucial for security.
Q214
Which service would you use for real-time data streaming?
AAmazon Kinesis
BAmazon S3
CAWS Lambda
DAmazon RDS
Explanation
Amazon Kinesis is designed specifically for real-time data streaming, while other services serve different data storage or execution purposes.
Q215
A company needs to deploy a machine learning model on mobile devices. Which AWS service should they use?
AAmazon SageMaker
BAWS Greengrass
CAWS Batch
DAmazon Comprehend
Explanation
AWS Greengrass enables local execution of machine learning models on mobile and IoT devices, unlike other options that are not optimized for mobile deployment.
Q216
You are configuring IAM policies for data access. What happens when both allow and deny policies are applied?
AAllow overrides deny policy
BDeny overrides allow policy
CBoth policies are ignored
DAccess is granted in all cases
Explanation
In IAM policies, a deny policy always takes precedence over allow policies, enforcing stricter access control.
Q217
Which service is best for deploying ML models at scale?
AAmazon SageMaker
BAWS Glue
CAmazon Aurora
DAWS Lambda
Explanation
Amazon SageMaker is designed specifically for ML model deployment, whereas the others serve different purposes.
Q218
A company needs to preprocess a large dataset for training without manual intervention. What is the best approach?
AUse Amazon SageMaker Data Wrangler
BImplement a Lambda function
CUtilize Amazon EMR
DEmploy AWS Step Functions
Explanation
Amazon EMR is ideal for processing large datasets in distributed environments, while others do not focus primarily on large-scale data preprocessing.
Q219
What happens when you decrease the instance type in a SageMaker endpoint?
ACosts decrease but inference delay increases
BCosts increase and performance improves
CInference delay decreases and costs remain
DPerformance is unaffected while costs increase
Explanation
Lower instance types reduce costs but can result in slower inference response times compared to higher types.
Q220
Which service is optimized for real-time event processing?
AAmazon Kinesis
BAmazon S3
CAWS Lambda
DAmazon Redshift
Explanation
Amazon Kinesis is designed for real-time data streaming, while S3, Lambda, and Redshift are for storage and batch processing.