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AWS Certified Machine Learning Engineer – Associate Exam (MLA-C01) - AWS Exam Questions
Last updated on June 20, 2026
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1
Question
An ML engineer is analyzing a classification dataset before training a model in Amazon SageMaker AI. The ML engineer suspects that the dataset has a significant imbalance between class labels that could lead to biased model predictions. To confirm class imbalance, the ML engineer needs to select an appropriate pre-training bias metric.
Which metric will meet this requirement?
Which metric will meet this requirement?
Options
A
Structural similarity index measure (SSIM)
B
Difference in proportions of labels (DPL)
C
Silhouette score
D
Mean squared error (MSE)
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2
Question
A financial company receives a high volume of real-time market data streams from an external provider. The streams consist of thousands of JSON records every second. The company needs to implement a scalable solution on AWS to identify anomalous data points.
Which solution will meet these requirements with the LEAST operational overhead?
Which solution will meet these requirements with the LEAST operational overhead?
Options
A
Send real-time data to an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Create an AWS Lambda function to consume the queue messages. Program the Lambda function to start an AWS Glue extract, transform, and load (ETL) job for batch processing and anomaly detection.
B
Ingest real-time data into Amazon Kinesis data streams. Deploy an Amazon SageMaker endpoint
for real-time outlier detection. Create an AWS Lambda function to detect anomalies. Use the data
streams to invoke the Lambda function.
for real-time outlier detection. Create an AWS Lambda function to detect anomalies. Use the data
streams to invoke the Lambda function.
C
Ingest real-time data into Apache Kafka on Amazon EC2 instances. Deploy an Amazon SageMaker endpoint for real-time outlier detection. Create an AWS Lambda function to detect anomalies. Use the data streams to invoke the Lambda function.
D
Ingest real-time data into Amazon Kinesis data streams. Use the built-in RANDOM_CUT_FOREST function in Amazon Managed Service for Apache Flink to process the data streams and to detect data anomalies.
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3
Question
An ML engineer wants to deploy a workflow that processes streaming IoT sensor data and periodically retrains ML models. The most recent model versions must be deployed to production.
Which service will meet these requirements?
Which service will meet these requirements?
Options
A
Apache Spark
B
Amazon Managed Workflows for Apache Airflow (MWAA)
C
AWS Lambda
D
Amazon SageMaker Pipelines
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4
Question
An ML engineer is using Amazon SageMaker to train a deep learning model that requires distributed training. After some training attempts, the ML engineer observes that the instances are not performing as expected. The ML engineer identifies communication overhead between the training instances.
What should the ML engineer do to MINIMIZE the communication overhead between the instances?
What should the ML engineer do to MINIMIZE the communication overhead between the instances?
Options
A
Place the instances in the same VPC subnet. Store the data in the same AWS Region but in a different Availability Zone from where the instances are deployed.
B
Place the instances in the same VPC subnet but in different Availability Zones. Store the data in a different AWS Region from where the instances are deployed.
C
Place the instances in the same VPC subnet. Store the data in the same AWS Region and Availability Zone where the instances are deployed.
D
Place the instances in the same VPC subnet. Store the data in a different AWS Region from where the instances are deployed.
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5
Question
A company needs to run a batch data-processing job on Amazon EC2 instances. The job will run during the weekend and will take 90 minutes to finish running. The processing can handle interruptions. The company will run the job every weekend for the next 6 months.
Which EC2 instance purchasing option will meet these requirements MOST cost-effectively?
Which EC2 instance purchasing option will meet these requirements MOST cost-effectively?
Options
A
Dedicated Instances
B
Reserved Instances
C
On-Demand Instances
D
Spot Instances
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