AIF-C01 Guidelines for Responsible AI Practice Question
Exhibit
ModelBiasJobConfig:
Type: AWS::SageMaker::ModelBiasJobDefinition
Properties:
JobResources:
InstanceConfig:
InstanceType: ml.m5.large
InstanceCount: 1
ModelBiasBaselineConfig:
BaseliningJobName: !Ref BaselineJob
ModelBiasAppSpecification:
ImageUri: !Ref Image
StoppingCondition:
MaxRuntimeInSeconds: 3600Refer to the exhibit. A team is configuring a SageMaker Model Bias job. The baseline job has been completed. However, the bias job fails with a resource not found error. What is the most likely cause?
⚠ Common exam trap
AWS often tests the distinction between different error types (timeout vs. resource not found vs. permission denied) to see if candidates understand the specific cause-and-effect relationship between misconfigured parameters and the exact error message returned.
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 BaseliningJobName is incorrect
The bias job requires a reference to the completed baseline job to compare the training data against. If the BaseliningJobName parameter is incorrect or does not match the actual name of the completed baseline job, SageMaker will throw a 'ResourceNotFound' error because it cannot locate the specified baseline job. The error is not related to timeouts, instance types, or IAM permissions for describing the baseline job.
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 StoppingCondition is too short
Why it's wrong here
A short StoppingCondition would terminate the job early or leave it incomplete, producing a timeout or status failure rather than a resource-not-found error. It is tempting because stopping conditions do cause job failures, but that applies to runaway training jobs, not to a missing baseline artefact referenced by the bias job.
- ✓
The BaseliningJobName is incorrect
Why this is correct
The bias job references the completed baseline by name; if BaseliningJobName does not match the actual baseline job, SageMaker cannot locate the baseline artefacts and returns a resource not found error. The baseline itself succeeded, so configuration is the cause.
- ✗
The instance type ml.m5.large is not supported
Why it's wrong here
SageMaker Clarify bias jobs accept ml.m5.large and similar general-purpose instances, so an unsupported instance type would raise a validation error, not a resource-not-found error. It is tempting because instance-type mismatches do fail jobs, but that applies when the chosen type is genuinely unavailable in the configured Region.
- ✗
The IAM role lacks permissions to DescribeBaselineJob
Why it's wrong here
A missing DescribeBaselineJob permission returns an AccessDenied error, not resource-not-found, so IAM is not the cause here. It is tempting because IAM role gaps commonly break SageMaker jobs, and that would be the answer if the error message cited authorisation rather than a missing resource.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-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 AIF-C01 exam.