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Data Preparation for Machine LearningeasyMultiple ChoiceObjective-mapped

MLA-C01 Data Preparation for Machine Learning Practice Question

Exhibit

Refer to the exhibit. A data scientist is trying to run a SageMaker Processing job that reads data from an S3 bucket. The IAM role attached to the processing job has the following policy:

```json
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": "s3:GetObject",
            "Resource": "arn:aws:s3:::my-bucket/*"
        }
    ]
}
```

The job fails with an error: "Access Denied" when trying to list objects. What is the root cause?

A SageMaker Processing job fails with 'Access Denied' when listing objects in an S3 bucket, despite the IAM policy shown in the exhibit. What is the most likely cause?

⚠ Common exam trap

AWS often tests the distinction between `s3:ListBucket` (required for listing objects) and `s3:GetObject` (required for reading objects), leading candidates to incorrectly assume that having `s3:GetObject` alone is sufficient for all S3 read operations.

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 policy lacks `s3:ListBucket` permission.

The error 'Access Denied' when listing objects in an S3 bucket indicates that the IAM role used by the SageMaker Processing job lacks the `s3:ListBucket` permission. This permission is required for the `ListObjectsV2` API call, which is necessary to enumerate objects in the bucket. Even if the role has `s3:GetObject` and `s3:PutObject` permissions, without `s3:ListBucket`, the job cannot list the bucket contents and will fail with an access denied 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 policy lacks `s3:ListBucket` permission.

    Why this is correct

    ListBucket is required to list objects; GetObject alone is insufficient.

  • The role does not have a trust relationship with SageMaker.

    Why it's wrong here

    Trust relationship issues cause role assumption failures, not listing errors.

  • The bucket policy denies the access.

    Why it's wrong here

    While possible, the direct cause is the missing ListBucket permission in the role.

  • The bucket is in a different region.

    Why it's wrong here

    Region mismatch results in a different error message.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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Last reviewed: Jun 30, 2026

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