AI-102 Practice Question: Implement natural language processing solutions
A developer is deploying a custom text classification model in Azure AI Language. The model must be accessible via a REST API with low latency. Which TWO actions should the developer take?
⚠ Common exam trap
Many exam-takers confuse batch processing with real-time inference, assuming that any API endpoint can provide low latency, or they mistakenly think exporting to a Docker container is the standard way to expose a model via REST in Azure.
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
✓
Obtain the endpoint URL and primary key from Language Studio
The endpoint URL and primary key are required to authenticate and route REST API requests to the deployed model. Language Studio provides these credentials after the model is deployed to a real-time endpoint, enabling low-latency inference via the Azure AI Language API.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the batch processing API
Why it's wrong here
Batch processing is not low-latency.
- ✗
Export the model as a Docker container
Why it's wrong here
Export/import is not needed for deployment.
- ✓
Obtain the endpoint URL and primary key from Language Studio
Why this is correct
Endpoint URL and key are needed to call the API.
- ✓
Deploy the model to a real-time endpoint
Why this is correct
Real-time endpoint is required for low-latency REST API access.
- ✗
Deploy to a test endpoint in the Azure portal
Why it's wrong here
No 'test' endpoint exists.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft 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 AI-102 exam.