Practice Questions

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Question 1

What is the primary purpose of Azure AI Foundry?

A. To provide pre-trained computer vision models only
B. To host virtual machines for AI workloads
C. To provide a unified platform for building, customizing, and managing generative AI solutions
D. To replace Azure Machine Learning

✅ Correct Answer: C

Explanation:
Azure AI Foundry is a unified platform designed to help teams build, customize, deploy, and manage generative AI applications at scale. It does not replace Azure ML but complements it.

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Question 2

Which capability of Azure AI Foundry allows organizations to compare and select the most appropriate model for a specific use case?

A. Role-Based Access Control (RBAC)
B. Model catalog and benchmarking
C. Azure Monitor integration
D. Speech synthesis APIs

✅ Correct Answer: B

Explanation:
Azure AI Foundry includes a model catalog with tools to compare and benchmark multiple models, helping teams choose the best model based on performance, cost, or task suitability.

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Question 3

A development team wants to create an AI system that can autonomously perform tasks and collaborate with other AI components. Which Azure AI Foundry capability supports this scenario?

A. Image classification
B. Agent orchestration
C. Text analytics
D. Speech recognition

✅ Correct Answer: B

Explanation:
Azure AI Foundry supports AI agents and multi-agent workflows, enabling autonomous task execution and collaboration across agents.

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Question 4

Which feature makes Azure AI Foundry suitable for enterprise environments?

A. Open-source licensing
B. Built-in gaming engines
C. Governance, monitoring, and role-based access controls
D. Support for only a single AI model

✅ Correct Answer: C

Explanation:
Enterprise readiness comes from security, governance, RBAC, monitoring, and compliance controls, all of which are core features of Azure AI Foundry.

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Question 5

Which task can be performed using Azure AI Foundry?

A. Only training custom neural networks from scratch
B. Managing physical AI hardware
C. Fine-tuning generative AI models for domain-specific use cases
D. Replacing Azure App Service

✅ Correct Answer: C

Explanation:
Azure AI Foundry allows fine-tuning and optimization of generative AI models to adapt them to specific business or domain requirements.

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Question 6

What stage of the AI lifecycle is supported by Azure AI Foundry?

A. Only model training
B. Only deployment
C. Only monitoring
D. The full lifecycle from experimentation to production and monitoring

✅ Correct Answer: D

Explanation:
Azure AI Foundry supports the entire AI lifecycle, including experimentation, development, deployment, monitoring, and continuous improvement.

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Question 7

Which scenario best matches the use of Azure AI Foundry?

A. Classifying images of animals
B. Translating text between languages
C. Building an enterprise chatbot that uses multiple AI models and enforces governance
D. Running batch SQL queries

✅ Correct Answer: C

Explanation:
Azure AI Foundry is designed for complex generative AI scenarios, such as enterprise chatbots that require multiple models, orchestration, and governance.

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Question 8

How does Azure AI Foundry integrate with other Azure services?

A. It operates completely independently
B. It only integrates with Azure OpenAI
C. It integrates with services like Azure App Service, Cosmos DB, and Logic Apps
D. It replaces all other Azure AI services

✅ Correct Answer: C

Explanation:
Azure AI Foundry integrates deeply with the Azure ecosystem, allowing generative AI solutions to be embedded into broader applications and workflows.

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Question 9

Which feature helps control access and usage of AI resources in Azure AI Foundry?

A. Prompt engineering
B. Role-Based Access Control (RBAC)
C. Image tagging
D. Speech transcription

✅ Correct Answer: B

Explanation:
RBAC ensures that users and teams only have access to the resources and actions they are authorized to use, supporting secure enterprise deployments.

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Question 10

On the AI-900 exam, when should you select Azure AI Foundry as the correct answer?

A. When the question focuses on basic image processing
B. When the question mentions simple sentiment analysis
C. When the scenario describes building, managing, and governing generative AI applications at scale
D. When the question requires only translation services

✅ Correct Answer: C

Explanation:
Azure AI Foundry is the best choice when the scenario involves enterprise-scale generative AI, including model selection, agents, lifecycle management, and governance.

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Quick Exam Summary

If the question mentions:

• Generative AI
• Multiple models
• Agents or workflows
• Enterprise governance
• End-to-end AI lifecycle

👉 Think: Azure AI Foundry

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