AI-300 ML Model Lifecycle And Operations Practice Question
You need to monitor the data drift of a model deployed in Azure ML. What is the first step you must take?
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 Data Drift Monitor
You must create a Data Drift Monitor object linked to your target dataset and baseline dataset to begin tracking.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure Application Insights
Why it's wrong here
App Insights is for monitoring request latency and system health.
- ✗
Run a manual evaluation script
Why it's wrong here
While possible, it is not the built-in Azure ML feature for ongoing monitoring.
- ✓
Create a Data Drift Monitor
Why this is correct
Data Drift Monitor is the specific feature for tracking distribution changes.
- ✗
Enable Azure Monitor logs
Why it's wrong here
Azure Monitor logs are for generic telemetry, not specific data drift detection.
About these practice questions
This AI-300 question is part of Courseiva's 204-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-300 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-300 exam.