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ModelingmediumMultiple ChoiceObjective-mapped

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/training-data/*"
        },
        {
            "Effect": "Allow",
            "Action": [
                "sagemaker:CreateTrainingJob",
                "sagemaker:CreateModel"
            ],
            "Resource": "*"
        }
    ]
}
```

Refer to the exhibit. An IAM policy is attached to a SageMaker notebook instance. The data scientist runs a training job that reads from s3://my-bucket/training-data/ and writes to s3://my-bucket/output/. The training job fails with an access denied error. What is the most likely cause?

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 does not allow s3:PutObject on the output location

The training job fails because the IAM policy does not grant s3:PutObject permission to the output location (s3://my-bucket/output/). The policy likely only allows s3:PutObject on the training-data prefix. Option A is incorrect because sagemaker:CreateTrainingJob is not directly related to write access; the job can be created but execution fails. Option C is incorrect because InvokeEndpoint is used for real-time inference, not training. Option D is incorrect because the policy does allow s3:GetObject on the training data (as it permits read access to that prefix).

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 does not allow sagemaker:CreateTrainingJob

    Why it's wrong here

    The policy allows sagemaker:CreateTrainingJob on all resources.

  • The policy does not allow s3:PutObject on the output location

    Why this is correct

    The s3:PutObject action is restricted to the training-data prefix only.

  • The policy is missing the sagemaker:InvokeEndpoint action

    Why it's wrong here

    InvokeEndpoint is not needed for training jobs.

  • The policy does not allow s3:GetObject on the training data

    Why it's wrong here

    The policy does allow s3:GetObject on training-data.

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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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.