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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a web app named App1 that sends requests to a multimodal chat model deployment in a Microsoft Foundry project.
User messages can contain both text and images.
Currently, App1 includes image URL: as plain text inside the message content so the model cannot recognize them as images.
Traces show that the requests contain a single text message instead of a multimodal content array.
You need to send the message as a structured array that includes both the text portion and the image reference to ensure that the model can process the image correctly.
What should you do?

A) Place the image URL inside the System Message and set type to image_url so the model loads the image at initialization.
B) Encode the image to base64 and include the encoded data inside the content string of the user message.
C) Add the image URL to the request metadata section, so the model can resolve the processing issue automatically.
D) Set the user message content array to include items that have type: text and type: image_url.

2. You have a custom agent named Agent1.
You need to control access to and monitor activity for Agent1 by using Microsoft Foundry.
What should you do first?

A) Add Agent1to a Microsoft Foundry project.
B) Add Agent1 to the Microsoft Foundry playground.
C) Provision an Application Insights resource.
D) Create a Microsoft Foundry project.

3. You have a Microsoft Foundry project that uses Azure AI Search to ground an agent in internal documentation.
After a recent content update, users report that the agent's answers have become less accurate.
You need to identify whether the retrieved content is negatively influencing the model's generated responses.
Which observability signal should you review?

A) groundedness evaluation metrics
B) prediction drift metrics
C) indexer status and failure history
D) latency breakdown traces

4. Drag and Drop Question
You have a Microsoft Foundry project that uses Azure Content Understanding in Foundry Tools to analyze marketing videos.
Video segmentation is enabled.
You need to configure an analyzer to output a generated JSON field that describes the color scheme of each video segment.
How should you configure the analyzer? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

5. You have a Microsoft Foundry project named Project1.
Project1 contains an application that processes PDF vendor invoices.
You need to configure Azure Document Intelligence in Foundry Tools to generate a Markdown output that preserves the sections and table structure of the PDFs. The solution must minimize development effort.
What should you do?

A) Configure content=markdown when you analyze the document.
B) Configure output=figures when you analyze the PDF.
C) Increase the confidence threshold.
D) Set the output_content_format=ContentFormat.MARKDOWN value.

Solutions: