Azure Generative AI Applications, Retrieval and Evaluation Practice Test
Build your confidence for Azure Generative AI Applications, Retrieval and Evaluation. Practice the concepts, understand the answers, and strengthen your knowledge one question at a time.
Try a sample questionExam overview and details
Review Azure generative AI application development, prompting, retrieval-augmented generation, model deployment, and evaluation. The questions help people building or checking AI application knowledge consider grounding, output quality, safety, and operational requirements. Administered by Microsoft. Key domains include Azure AI Studio and Model Catalog, Azure OpenAI Service, Prompt Engineering and RAG and AI Solution Development and Deployment.
Sample Questions
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An enterprise assistant passes automated quality tests, but support tickets show users misunderstand when answers are generated versus quoted from policy. What product control helps?
A product team asks for a chatbot, but user interviews show that employees mostly need structured extraction from invoices. What should the architect recommend?
A retail company wants to classify store photos, summarize customer emails, and extract invoice fields. The sponsor asks for one "AI model" to do everything because all three are AI tasks. What is the best planning response?
A team needs low-cost summarization of short support chats and high-quality reasoning for escalated legal questions. What deployment strategy best balances cost and quality?
A mobile app asks users to upload a room photo and request design suggestions based on visible furniture. The app needs text advice, not a new image. Which capability is the best fit?
Career Opportunities & Salary
Exam insights and study advice
Generative AI applications require decisions about model use, retrieved context, evaluation, and safeguards throughout development.
What this exam covers
Use the published domain weights to plan your study. Practice results do not predict your certification exam score.
01Azure AI Studio and Model Catalog
Azure AI Studio interface, model catalog, project setup, and AI development environment
02Azure OpenAI Service
Azure OpenAI models, deployments, API usage, fine-tuning, and model management
03Prompt Engineering and RAG
Prompt engineering techniques, retrieval augmented generation, and prompt flow
04AI Solution Development and Deployment
Building, evaluating, and deploying AI solutions using Azure AI services
05Responsible AI and Safety
Content safety, responsible AI principles, fairness, reliability, and governance