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MLA-C01 Practice Question: Which THREE steps are part of the typical…
Which THREE steps are part of the typical workflow when using SageMaker built-in algorithms?
⚠ Common exam trap
Candidates often confuse the deployment step (setting up an endpoint) with the core training workflow, or think custom images are required for built-in algorithms, when in fact SageMaker handles the container automatically.
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
✓
Create a training job
Creating a training job is a fundamental step in the SageMaker workflow for built-in algorithms. You must specify the algorithm, input data location in S3, output path, and compute resources to start model training. Without a training job, no model artifact is generated for deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set up a real-time inference endpoint
Why it's wrong here
Inference endpoints are separate from training workflow.
- ✓
Create a training job
Why this is correct
A training job is required to start model training.
- ✗
Create a custom training image
Why it's wrong here
Built-in algorithms come with pre-built Docker images; no custom image needed.
- ✓
Set hyperparameters
Why this is correct
Hyperparameters must be specified to configure the algorithm.
- ✓
Monitor training with CloudWatch
Why this is correct
Monitoring metrics via CloudWatch is a standard practice during training.
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 MLA-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 MLA-C01 exam.