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MLS-C01 Modeling Practice Question

Exhibit

Refer to the exhibit.

$ aws sagemaker create-training-job \
    --training-job-name my-job \
    --algorithm-specification TrainingImage=382416733822.dkr.ecr.us-west-2.amazonaws.com/xgboost:latest,TrainingInputMode=File \
    --role-arn arn:aws:iam::123456789012:role/SageMakerRole \
    --input-data-config "[{\"ChannelName\": \"train\", \"DataSource\": {\"S3DataSource\": {\"S3DataType\": \"S3Prefix\", \"S3Uri\": \"s3://my-bucket/train/\", \"S3DataDistributionType\": \"FullyReplicated\"}}}]" \
    --output-data-config "{\"S3OutputPath\": \"s3://my-bucket/output/\"}" \
    --resource-config "{\"InstanceType\": \"ml.m5.large\", \"InstanceCount\": 1}" \
    --stopping-condition "{\"MaxRuntimeInSeconds\": 86400}"

Refer to the exhibit. A data scientist runs the AWS CLI command to create a SageMaker training job. The job fails immediately with 'ValidationException: Invalid instance type'. What is the most likely issue?

⚠ Common exam trap

A common mix-up: candidates assume 'Invalid instance type' always means the instance is unsupported by the algorithm, when in reality SageMaker uses this generic error for any validation failure related to the training job's resource configuration, including regional mismatches in the image URI.

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 training image URI is for a different AWS region

The error 'ValidationException: Invalid instance type' occurs because the training image URI specified in the command points to an Amazon ECR repository in a different AWS region than where the SageMaker training job is being created. SageMaker validates that the image URI is accessible from the current region; if the URI references a region that does not contain the XGBoost image or the instance type is not supported in that region's ECR, the validation fails. The instance type itself (ml.m5.large) is valid for XGBoost, but the mismatch between the image's region and the job's region triggers the exception.

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 ARN is invalid

    Why it's wrong here

    Would cause AccessDenied.

  • The S3 bucket 'my-bucket' does not exist or the role lacks permissions

    Why it's wrong here

    Would cause AccessDenied, not ValidationException.

  • The instance type ml.m5.large does not support the XGBoost image

    Why it's wrong here

    XGBoost supports ml.m5.large.

  • The training image URI is for a different AWS region

    Why this is correct

    The account ID corresponds to us-east-1, but the CLI command is running in us-west-2.

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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.