AI-300 Practice Question: Generative AI Quality Assurance And Observability
Which THREE actions are essential when managing a 'Golden Dataset' for LLM evaluation?
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
✓
Versioning the dataset to track changes
Curating high-quality data, versioning it, and periodically updating it are key management activities.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Versioning the dataset to track changes
Why this is correct
Versioning ensures reproducibility.
- ✗
Encrypting the data with public keys only
Why it's wrong here
Encryption practices vary; not a specific management task.
- ✗
Deleting logs after each test run
Why it's wrong here
Logs are required for comparison.
- ✓
Updating the dataset as model capabilities change
Why this is correct
Datasets must stay relevant to the application version.
- ✓
Curating high-quality prompt-response pairs
Why this is correct
Data quality is critical.
About these practice questions
One of 204 original AI-300 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. 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.