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.
A company needs to predict customer churn based on historical data. Which AWS service is best suited for this task?
AAmazon SageMaker
BAWS Lambda
CAmazon Athena
DAmazon SNS
Explanation
Amazon SageMaker provides a comprehensive environment for building, training, and deploying machine learning models, unlike the other services listed.
Q372
You are configuring a machine learning model in Amazon Sagemaker and encounter a hyperparameter tuning job. What happens if the maximum number of training jobs is reached?
ATraining stops automatically
BJobs continue until manually stopped
CJobs are queued until space available
DNew jobs overwrite existing ones
Explanation
Once the maximum is reached, the training stops automatically; new jobs cannot continue until tuned parameters are adjusted.
Q373
A company needs to improve model predictions by training with additional data. Which AWS service can streamline model training with automatic scaling and distributed computing?
AAmazon SageMaker
BAWS Glue
CAmazon Athena
DAWS Lambda
Explanation
Amazon SageMaker simplifies model training and scales automatically; AWS Glue is for data preparation, Athena is for querying data, and Lambda is serverless computing not focused on training models.
Q374
What happens when you use Amazon S3 Intelligent-Tiering storage class for infrequently accessed data?
AData is archived immediately
BCosts are reduced automatically
CData is deleted immediately
DData is inaccessible until tiered
Explanation
Amazon S3 Intelligent-Tiering optimizes costs by moving data based on access patterns; options A, C, and D misrepresent its functionality.
Q375
You are configuring an Amazon SageMaker endpoint. Which parameter helps you manage variations in incoming request traffic to maintain performance?
AInstance Type
BEndpoint Configuration
CAuto Scaling
DModel Training
Explanation
Auto Scaling allows dynamic adjustment of resources for varying traffic; the other options do not specifically address performance management for request variations.
Q376
A company needs to analyze the sentiment of customer reviews using machine learning. Which AWS service is best suited for this task?
AAmazon Comprehend
BAmazon Rekognition
CAmazon Lex
DAmazon Polly
Explanation
Amazon Comprehend is designed for natural language processing tasks like sentiment analysis, while others are for different functionalities.
Q377
What happens when you use a very small batch size for training a deep learning model on Amazon SageMaker?
AFaster convergence
BToo much overfitting
CIncreased training time
DLower memory consumption
Explanation
Using a small batch size can lead to higher variance in parameter updates, resulting in overfitting. The other options are not typically true.
Q378
You are configuring AWS IAM roles for a machine learning application. How can you ensure least privilege access?
AApply broad permissions to all services
BGive full access for simplicity
CLimit actions to only what is necessary
DUse root account for all operations
Explanation
Limiting actions to what is necessary ensures least privilege, while the other options compromise security.
Q379
Which service facilitates data labeling for machine learning models?
AAmazon SageMaker Ground Truth
BAWS Glue
CAmazon Athena
DAWS Step Functions
Explanation
Amazon SageMaker Ground Truth offers data labeling services, while the others pertain to data processing and orchestration.
Q380
A company needs to store large datasets with frequent updates for real-time queries. Which storage solution is the most suitable?
AAmazon S3
BAmazon RDS
CAmazon DynamoDB
DAmazon EFS
Explanation
Amazon DynamoDB is designed for high-velocity updates and queries, whereas the others do not handle such usage effectively.