MLS-C01 Modeling Practice Question

Exhibit

Refer to the exhibit.

```
aws sagemaker create-training-job \
    --training-job-name my-job \
    --algorithm-specification TrainingImage=123456789012.dkr.ecr.us-east-1.amazonaws.com/my-image:latest,TrainingInputMode=File \
    --role-arn arn:aws:iam::123456789012:role/SageMakerRole \
    --input-data-config '[{"ChannelName": "train", "DataSource": {"S3DataSource": {"S3DataType": "S3Prefix", "S3Uri": "s3://bucket/train/"}}}]' \
    --output-data-config S3OutputPath=s3://bucket/output/ \
    --resource-config InstanceType=ml.c5.xlarge,InstanceCount=1,VolumeSizeInGB=10 \
    --stopping-condition MaxRuntimeInSeconds=3600
```

Refer to the exhibit. A data scientist runs the above CLI command to create a SageMaker training job. The job fails with an error 'Unable to read data from s3://bucket/train/'. What is the MOST likely cause?

⚠ Common exam trap

It's easy for candidates to confuse the error message with a network or region issue, but the 'Unable to read data' error is almost always an IAM permissions problem, not a connectivity or resource constraint issue.

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 IAM role does not have permissions to read from the S3 bucket

The error 'Unable to read data from s3://bucket/train/' indicates that the SageMaker training job cannot access the S3 input data. The most common cause is that the IAM role specified in the command does not have the necessary s3:GetObject permission on the S3 bucket or objects. SageMaker uses the IAM role to assume permissions for reading training data, and without proper S3 read access, the job fails at the data loading stage.

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 image is not accessible
Why it's wrong here
Image accessibility would cause a different error (e.g., 'Unable to pull image').
✗
The instance type does not support the required memory
Why it's wrong here
Instance memory would cause an out-of-memory error, not a data read error.
✓
The IAM role does not have permissions to read from the S3 bucket
Why this is correct
The role must have s3:GetObject permission for the training data.
✗
The training job is in a different region than the S3 bucket
Why it's wrong here
S3 is region-agnostic for access, but cross-region access requires explicit permission; however, the error message suggests a permission 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

1 more way this is tested on MLS-C01

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A data scientist is trying to create a SageMaker training job but receives an access denied error. The IAM policy attached to the role is shown in the exhibit. What is the most likely cause of the error?

medium

✓ A.The policy does not allow s3:PutObject for the output location
B.The policy does not allow sagemaker:CreateTrainingJob
C.The policy has an explicit deny on s3:PutObject
D.The policy does not allow s3:GetObject on the output bucket

Why A: The IAM policy attached to the role must include the s3:PutObject action to allow SageMaker to write the training output to the specified S3 bucket. Without this permission, the training job fails with an access denied error. Option B is incorrect because the policy likely includes sagemaker:CreateTrainingJob permission, which is necessary to start the job. Option C is incorrect because there is no explicit deny statement in the policy. Option D is incorrect because the training job needs to write output, not read from the output bucket; s3:GetObject is not required for the output location.

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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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.