MLS-C01 Modeling Practice Question
Exhibit
Refer to the exhibit.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3:GetObject",
"s3:PutObject"
],
"Resource": "arn:aws:s3:::my-bucket/train/*"
},
{
"Effect": "Allow",
"Action": [
"sagemaker:CreateTrainingJob",
"sagemaker:DescribeTrainingJob"
],
"Resource": "*"
}
]
}An IAM policy attached to a SageMaker execution role is shown. A training job executed with this role fails with an error that the role cannot access the S3 bucket. The training job uses input data from s3://my-bucket/train/data.csv and output to s3://my-bucket/output/. What is the most likely cause?
⚠ Common exam trap
AWS often tests the distinction between read and write permissions in SageMaker S3 access, and the trap here is that candidates assume the error is about reading input data (Option A) when the actual failure is due to missing write permissions for the output location (Option C).
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The training job does not have s3:PutObject permission for the output location
The error message indicates the role cannot access the S3 bucket, which typically occurs when the role lacks write permissions to the output location. The training job needs s3:PutObject permission to write the output artifacts (model, logs, etc.) to s3://my-bucket/output/. Without this permission, SageMaker fails to save the training results, resulting in an access error.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The training job does not have s3:GetObject permission for the input data
Why it's wrong here
The policy allows s3:GetObject on train/*, which includes the input data.
- ✗
The training data is encrypted with SSE-KMS and the role lacks KMS permissions
Why it's wrong here
No KMS permissions are in the policy, but the error is about S3 access, not KMS.
- ✓
The training job does not have s3:PutObject permission for the output location
Why this is correct
The output path 'output/' is not covered by the resource 'train/*', so PutObject fails.
- ✗
The S3 bucket is in a different region than the training job
Why it's wrong here
Region mismatch could cause errors, but the policy is the more direct issue.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.