AI0-001 AI Infrastructure and Technologies Practice Question
A company has a TensorFlow model trained on-premises and wants to deploy it on AWS SageMaker for scalable inference. What is the BEST way to package the model for deployment?
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
✓
Package the model in a Docker container with a TensorFlow serving script and push to Amazon ECR
SageMaker expects models in a container format; the inference container should include the model artifacts and the serving code, allowing SageMaker to host it on scalable endpoints.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert the model to ONNX and upload to SageMaker
Why it's wrong here
ONNX is an intermediate format; SageMaker still needs a container to host it.
- ✗
Upload the .h5 file to S3 and create a SageMaker endpoint directly
Why it's wrong here
A SageMaker endpoint requires a container that knows how to load and serve the model, not just the raw file.
- ✓
Package the model in a Docker container with a TensorFlow serving script and push to Amazon ECR
Why this is correct
This creates an inference container that SageMaker can deploy; it includes the model and serving logic.
- ✗
Use SageMaker Studio to train the model again from scratch
Why it's wrong here
Retraining is unnecessary and wasteful; the existing model can be deployed.
About these practice questions
Courseiva writes every AI0-001 question from scratch — 754 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.