AIF-C01 Fundamentals of AI and ML Practice Question
A company wants to use Amazon SageMaker to train a model using a custom Docker container that has specific dependencies. The training code is stored in an S3 bucket. Which steps must be taken to run the training job?
⚠ Common exam trap
AWS often tests the misconception that any S3-uploaded artifact (including Docker images) can be directly referenced in a training job, but SageMaker strictly requires container images to be stored in ECR, not S3.
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
✓
Push the custom container to Amazon ECR and create a training job with the container URI
Amazon SageMaker requires custom Docker containers to be stored in Amazon Elastic Container Registry (ECR) to run training jobs. The container URI from ECR is specified in the `AlgorithmSpecification` parameter of the `CreateTrainingJob` API call, allowing SageMaker to pull and execute the container with the training code from S3. Option B correctly describes this mandatory workflow.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Install dependencies via SageMaker's lifecycle configuration instead of a custom container
Why it's wrong here
Lifecycle configurations apply to notebooks, not training jobs.
- ✓
Push the custom container to Amazon ECR and create a training job with the container URI
Why this is correct
ECR is the correct registry for Docker images used in SageMaker.
- ✗
Use SageMaker's built-in framework container and override the entry point
Why it's wrong here
A custom container is specifically requested, so built-in containers are insufficient.
- ✗
Upload the container to S3 and reference it in the training job
Why it's wrong here
Containers must be stored in Amazon ECR, not S3.
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 |
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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.