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Amazon MLA-C02 Dumps

Amazon MLA-C02 Practice Exam Questions

AWS Certified Machine Learning Engineer - Associate

Total Questions : 207
Update Date : October 30, 2026
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Amazon MLA-C02 Sample Question Answers

Question # 1

A SageMaker AI training job must read only from s3://ml-data/fraud/ and write only to s3://ml-models/fraud/. How should the ML engineer apply least privilege?

A. Use the root user's access keys in the training script.
B. Attach a policy to the job's execution role that allows s3:GetObject on the input prefix and s3:PutObject on the output prefix only.
C. Make both buckets public.
D. Attach the AmazonS3FullAccess managed policy to the execution role.



Question # 2

A company requires that traffic between its applications and Amazon Bedrock and SageMaker AI never traverses the public internet. Which actions should the ML engineer take? (Select TWO.)

A. Use security groups that allow only the required traffic to the endpoints.
B. Create interface VPC endpoints (AWS PrivateLink) for the Bedrock and SageMaker Runtime APIs.
C. Place the applications in public subnets with an internet gateway.
D. Share root credentials with application servers.
E. Disable TLS on all connections.



Question # 3

Match each AWS service to the security or compliance task it performs.Drag each lettered description to the matching numbered item. Each letter is used once.Item:1. AWS CloudTrail2. AWS Config3. Amazon Inspector4. Amazon MacieDescription:A. Discovers sensitive data in Amazon S3B. Evaluates resource configurations against compliance rulesC. Records API activity for auditingD. Scans container images and workloads for vulnerabilities



Question # 4

A SageMaker AI training job fails with an AccessDenied error when it reads training data from an S3 bucket that is encrypted with a customer managed KMS key. The execution role already allows s3:GetObject. What is the MOST likely fix?

A. Allow the execution role to use kms:Decrypt in both the role policy and the KMS key policy.
B. Disable encryption on the bucket.
C. Add s3:PutBucketPolicy to the execution role.
D. Change the training instance type.



Question # 5

A company must continuously check that every SageMaker AI endpoint configuration uses a customer managed KMS key, and must flag any configuration that does not. Which service should the ML engineer use?

A. Amazon Macie
B. AWS X-Ray
C. AWS Config rules
D. AWS Budgets



Question # 6

Before deployment, every custom inference container image in Amazon ECR must be scanned for operating system and package vulnerabilities. Which service should the ML engineer use?

A. Amazon Inspector
B. AWS Shield
C. Amazon Macie
D. Amazon GuardDuty



Question # 7

Which safeguards can be configured in Amazon Bedrock Guardrails? (Select THREE.)

A. Hyperparameter search ranges
B. Content filters for categories such as hate, insults, and violence
C. Sensitive information (PII) filters
D. SHAP feature attributions
E. Denied topics



Question # 8

A SageMaker Pipelines processing step needs a database password. The password must not appear in code or environment variable definitions and must rotate automatically. Where should the ML engineer store it?

A. An S3 object with public read access
B. A plaintext file in the Git repository
C. A hard-coded string in the processing script
D. AWS Secrets Manager with automatic rotation, retrieved at runtime by the execution role



Question # 9

A Bedrock application sometimes returns customers' phone numbers and email addresses in its responses. The company wants this information masked automatically. What should the ML engineer use?

A. AWS KMS key rotation
B. AWS WAF IP set rules
C. Sensitive information filters in Amazon Bedrock Guardrails configured to mask PII
D. Amazon S3 Object Lock



Question # 10

A production SageMaker AI endpoint was deleted unexpectedly. The security team must find out who deleted it and when. Which service provides this information?

A. AWS CloudTrail
B. AWS X-Ray
C. Amazon Inspector
D. Amazon CloudWatch metrics