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MLA-C01 AWS Certified Machine Learning Engineer - Associate

  • Amazon
  • 5 free sample questions

About this exam

MLA-C01 is the Amazon exam AWS Certified Machine Learning Engineer - Associate. Paid practice material for this exam is not available yet, but you can try its free sample questions.

Exam code
MLA-C01
Vendor
Amazon
Practice questions
Not available yet
Free sample questions
5
Question bank last updated
Not available yet

Try 2 sample questions

Taken from the free sample set for MLA-C01.

Question 1

A company is using an Amazon Redshift database as its single data source. Some of the data is sensitive.

A data scientist needs to use some of the sensitive data from the database. An ML engineer must give the data scientist access to the data without transforming the source data and without storing anonymized data in the database.

Which solution will meet these requirements with the LEAST implementation effort?

  1. Option A:

    Configure dynamic data masking policies to control how sensitive data is shared with the data scientist at query time.

  2. Option B:

    Create a materialized view with masking logic on top of the database. Grant the necessary read permissions to the data scientist.

  3. Option C:

    Unload the Amazon Redshift data to Amazon S3. Use Amazon Athena to create schema-on-read with masking logic. Share the view with the data scientist.

  4. Option D:

    Unload the Amazon Redshift data to Amazon S3. Create an AWS Glue job to anonymize the data. Share the dataset with the data scientist.

Show answer and explanation

Correct answer: A

Dynamic data masking allows you to control how sensitive data is presented to users at query time, without modifying or storing transformed versions of the source data. Amazon Redshift supports dynamic data masking, which can be implemented with minimal effort. This solution ensures that the data scientist can access the required information while sensitive data remains protected, meeting the requirements efficiently and with the least implementation effort.

Question 2 (choose 2)

A company is developing an application that reads animal descriptions from user prompts and generates images based on the information in the prompts. The application reads a message from an Amazon Simple Queue Service (Amazon SQS) queue. Then the application uses Amazon Titan Image Generator on Amazon Bedrock to generate an image based on the information in the message. Finally, the application removes the message from SQS queue.

Which IAM permissions should the company assign to the application ' s IAM role? (Select TWO.)

  1. Option A:

    Allow the bedrock:InvokeModel action for the Amazon Titan Image Generator resource.

  2. Option B:

    Allow the bedrock:Get* action for the Amazon Titan Image Generator resource.

  3. Option C:

    Allow the sqs:ReceiveMessage action and the sqs:DeleteMessage action for the SQS queue resource.

  4. Option D:

    Allow the sqs:GetQueueAttributes action and the sqs:DeleteMessage action for the SQS queue resource.

  5. Option E:

    Allow the sagemaker:PutRecord* action for the Amazon Titan Image Generator resource.

Show answer and explanation

Correct answer: A, C

To generate images, the application must invoke a foundation model hosted on Amazon Bedrock. Invoking the Amazon Titan Image Generator requires the bedrock:InvokeModel permission. Read-only permissions such as bedrock:Get* do not allow inference execution and are insufficient.

The application also interacts with Amazon Simple Queue Service. To process messages, the application must be able to receive messages from the queue and delete them after successful processing. These actions require sqs:ReceiveMessage and sqs:DeleteMessage.

sqs:GetQueueAttributes alone does not allow message consumption. SageMaker permissions are unrelated because Bedrock is a separate service.

Therefore, permissions to invoke the model and receive/delete SQS messages are required.

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