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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. Hotspot Question
You have a Microsoft Foundry project that contains a deployed chat model.
You have a Python service that sends API requests to the model. The service is integrated with an automated validation system that compares generated outputs against approved response patterns.
Stakeholders report that small wording differences are causing validation mismatches.
You need to update the request parameters to improve output stability. The solution must maximize reasoning quality.
How should you complete the Python code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

2. You have an app named App1 that uses a Microsoft Foundry multimodal model deployment.
App1 runs optical character recognition (OCR) on uploaded images and appends the OCR output to the prompt as additional context.
Some uploaded images contain embedded text.
You need to prevent potentially malicious instructions from being processed by the model.
What should you use?

A) prompt shields for documents
B) prompt shields for user prompts
C) protected material text
D) image moderation

3. Hotspot Question
You have a Microsoft Foundry project that contains a customer support agent built by using the Foundry Agent Service.
The agent uploads user-provided screenshots to Azure Storage through a ticketing tool and receives a blob URL for additional reasoning.
You need to use image moderation during agent runs and prevent harmful content from being returned during runs. Azure AI Content Safety must access the images by using the blob URL.
The solution must follow the principle of least privilege.
What should you configure for Content Safety? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

4. You have an Azure subscription that contains an Azure OpenAI resource.
You need to build an app that will suggest product names from a given product description.
Which model should you use?

A) Whisper
B) embeddings
C) GPT-4
D) DALL-E

5. An agent must call your organisation's internal inventory system, which is exposed as a set of tools. You want the tool definitions maintained centrally and reusable across several agents rather than redefined in each agent. Which Foundry capability fits?

A) Add a Model Context Protocol (MCP) server as an agent tool
B) Fine-tune the model on the inventory system's API schema
C) Increase the model's context window
D) Enable the code interpreter tool

Solutions: