AI-300 Practice Question: Generative AI Quality Assurance And Observability
You are setting up an evaluation suite for your LLM. Which THREE metrics are commonly provided by the 'Built-in' evaluators in Azure AI Prompt Flow?
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
✓
Coherence
The standard built-in metrics in Prompt Flow include Groundedness, Relevance, and Coherence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Coherence
Why this is correct
Built-in metric.
- ✓
Groundedness
Why this is correct
Built-in metric.
- ✓
Relevance
Why this is correct
Built-in metric.
- ✗
Deployment cost
Why it's wrong here
Not an evaluation metric.
- ✗
Training duration
Why it's wrong here
Not an output quality metric.
About these practice questions
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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.