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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a Microsoft Foundry project.
You need to deploy a model from the model catalog to support a search solution for internal policy documents. The model must generate vector representations of the text in the documents and of user queries.
Which type of model should you use?

A) an image generation model
B) a small language model (SLM)
C) an embedding model
D) a large language model (LLM)

2. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content.
You need to improve response completeness.
Solution: You run an evaluation flow that scores responses for completeness and blocks responses that fall below a defined threshold.
Does this meet the goal?

A) Yes
B) No

3. You are creating an image-editing workflow in a Microsoft Foundry project.
The workflow must meet the following requirements:
- Ensure that background objects can be removed by applying a mask-
based inpainting edit.
- Preserve the original lighting and style of the edited images.
- Use the built-in image editing controls, NOT a custom model.
You need to ensure that image edits apply exclusively inside the masked area.
How should you configure the workflow?

A) Enable image_to_image mode and a high-strength value to regenerate the full image based on the prompt.
B) Enable text_to_image mode and a prompt describing the desired background removal.
C) Set generation mode to image_variation and provide the original image as a reference.
D) Enable mask_inpainting and supply both the input image and a mask indicating which part of the image to modify.

4. You have a custom named entity recognition (NER) project in Azure Language in Foundry Tools for support tickets. The schema for the project contains an entity type named ContactInfo.
In tagged training files, ContactInfo is used for phone numbers, email addresses, and social media handles.
Model evaluation shows low precision for ContactInfo, including false positives in which nearby text is extracted as ContactInfo.
You need to improve the precision of the project.
What should you do before retraining the model?

A) Add more support tickets as training data and label more ContactInfo entities.
B) Trigger an auto-labeling job.
C) Replace ContactInfo by using Phone, Email, and SocialMedia entities. Relabel every matching span.
D) Lower the confidence threshold for ContactInfo.

5. Hotspot Question
You have a Python application collects customer comments before posting them to a public forum.
You need to send a text comment to Azure AI Content Safety and return the self-harm severity from the response.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Solutions: