AI-102 Practice Question: Implement natural language processing solutions
Which THREE components are required to deploy a bot using Azure AI Language's conversational language understanding (CLU) and Azure Bot Service?
⚠ Common exam trap
Watch out — candidates often assume QnA Maker or Translator are mandatory for a CLU-based bot, but CLU itself provides intent recognition and can be extended with other services only as needed, not as prerequisites.
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
✓
An Azure Bot Service bot with the CLU model as a skill.
Azure Bot Service can integrate a CLU model as a skill, enabling the bot to route user intents to the CLU service for natural language understanding. This is done by configuring the bot's skill endpoint to point to the CLU project's prediction URL, allowing the bot to leverage the trained model for intent classification and entity extraction.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
An Azure Bot Service bot with the CLU model as a skill.
Why this is correct
The bot interacts with users and uses the CLU model.
- ✓
A CLU project and a trained model.
Why this is correct
Provides intent and entity recognition.
- ✗
A QnA Maker resource for FAQs.
Why it's wrong here
Not required; CLU can handle FAQs.
- ✗
A Translator resource for multilingual support.
Why it's wrong here
Not required; CLU can handle multiple languages.
- ✓
A Microsoft Entra ID app registration for the bot.
Why this is correct
Required for authentication in channels like Teams.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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