AI-103 Implement Generative AI And Agentic Solutions Practice Question
Which THREE features are provided by the Azure AI Foundry evaluation service?
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
✓
Visualization of evaluation results
Built-in metrics, custom evaluation logic, and dataset visualization are key features.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Visualization of evaluation results
Why this is correct
Results are visualized in the portal.
- ✓
Built-in metrics for RAG (e.g., coherence, fluency)
Why this is correct
These are native evaluation metrics.
- ✗
Automated model fine-tuning based on failures
Why it's wrong here
Fine-tuning is a separate process.
- ✓
Custom evaluation code integration
Why this is correct
Users can write custom python evaluators.
- ✗
Automatic user interface generation
Why it's wrong here
Evaluation does not generate UIs.
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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-103 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-103 exam.