This MLS-C01 practice question tests your understanding of modeling. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Exhibit
Refer to the exhibit.
```
[Container] Training completed.
[Container] Uploading model artifacts to S3: s3://my-bucket/model.tar.gz
[Container] Training job completed
```
Refer to the exhibit. The log shows the end of a successful SageMaker training job. However, the ML engineer cannot find the model artifacts in the specified S3 bucket. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Refer to the exhibit.
```
[Container] Training completed.
[Container] Uploading model artifacts to S3: s3://my-bucket/model.tar.gz
[Container] Training job completed
```
A
The IAM role used by the training job does not have permission to write to the S3 bucket.
Without s3:PutObject, the upload fails.
B
The S3 bucket does not exist.
Why wrong: The job would have failed before training.
C
The model artifacts were uploaded to a different S3 path.
Why wrong: The log shows the correct path.
D
The training job did not have network access to S3.
Why wrong: Network access is typically configured; lack would cause other errors.
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 used by the training job does not have permission to write to the S3 bucket.
The training job completed successfully, meaning the SageMaker training container executed without errors. However, if the model artifacts are not found in the specified S3 bucket, the most likely cause is that the IAM role associated with the training job lacks the necessary s3:PutObject permission for that bucket. SageMaker uses the role's credentials to write the output; without write access, the artifacts are silently dropped or fail to upload, even though the training code itself may have run to completion.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 IAM role used by the training job does not have permission to write to the S3 bucket.
Why this is correct
Without s3:PutObject, the upload fails.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The S3 bucket does not exist.
Why it's wrong here
The job would have failed before training.
✗
The model artifacts were uploaded to a different S3 path.
Why it's wrong here
The log shows the correct path.
✗
The training job did not have network access to S3.
Why it's wrong here
Network access is typically configured; lack would cause other errors.
Common exam traps
Common exam trap: answer the scenario, not the keyword
AWS often tests the misconception that a successful training job log implies the model artifacts were successfully uploaded, when in fact the IAM role permissions are the gatekeeper for S3 write operations, and a missing permission can cause silent failures.
Trap categories for this question
Command / output trap
The log shows the correct path.
Detailed technical explanation
How to think about this question
SageMaker training jobs use the IAM execution role passed in the CreateTrainingJob API call to authenticate S3 operations. The role must have an IAM policy granting s3:PutObject on the output bucket and prefix. Under the hood, the SageMaker container calls the AWS SDK to upload the model.tar.gz file; if the role lacks permissions, the upload silently fails or throws a permission error that may be logged but not cause the training script to exit with a non-zero code. In real-world scenarios, engineers often overlook granting write access to cross-account buckets or buckets with S3 Object Ownership settings that require explicit bucket policy statements.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The IAM role used by the training job does not have permission to write to the S3 bucket. — The training job completed successfully, meaning the SageMaker training container executed without errors. However, if the model artifacts are not found in the specified S3 bucket, the most likely cause is that the IAM role associated with the training job lacks the necessary s3:PutObject permission for that bucket. SageMaker uses the role's credentials to write the output; without write access, the artifacts are silently dropped or fail to upload, even though the training code itself may have run to completion.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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