AI-300 ML Model Lifecycle And Operations Practice Question
Which THREE metrics can be logged during training to track performance in Azure ML?
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
✓
Model accuracy.
Accuracy, loss, and custom metrics are standard loggable items.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Model accuracy.
Why this is correct
Standard metric.
- ✗
Compute instance IP address.
Why it's wrong here
Not a performance metric.
- ✓
Custom metrics.
Why this is correct
Supported via SDK.
- ✗
Workspace subscription ID.
Why it's wrong here
Not a performance metric.
- ✓
Training loss.
Why this is correct
Standard metric.
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.