AI-102 Practice Question: Implement natural language processing solutions
You are building a custom question answering solution using Azure AI Language. Which TWO actions are required to deploy the solution?
⚠ Common exam trap
Watch out — candidates often confuse the legacy QnA Maker service with the current Azure AI Language Custom Question Answering feature, or assume that custom model training is required when the service uses a pre-trained extractive model.
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 Custom Question Answering project in Azure AI Language.
A Custom Question Answering project is the container for your question-answer pairs, synonyms, and active learning settings within Azure AI Language. You must create this project to define the knowledge base that the solution will query against.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a Custom Question Answering project in Azure AI Language.
Why this is correct
This is the first step.
- ✗
Train a custom model using the Azure AI Language training API.
Why it's wrong here
Training is automatic upon adding data.
- ✗
Create a QnA Maker service in the Azure portal.
Why it's wrong here
QnA Maker is deprecated; use Azure AI Language.
- ✓
Deploy the project to an Azure AI Language resource.
Why this is correct
Deployment makes the model available.
- ✗
Publish the project to a web app bot.
Why it's wrong here
Optional step.
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JA
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.