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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question 1

You have a Microsoft Foundry project that contains a Retrieval Augmented Generation (RAG) chat solution used by customer support agents.
You are adding an automated pre-production evaluation step to a CI/CD pipeline named Pipeline1. The evaluation will run against a labeled test dataset that contains support questions and the expected grounding context.
You need to ensure that Pipeline1 fails if unsupported content or a retrieval mismatch exceeds a defined threshold:
- responses include claims not supported by the retrieved source
content
- retrieved source content does not align with the labeled expected
context
Which two built-in evaluators should you use in Pipeline1? Each correct answer presents pat of the solution.
NOTE: Each correct selection is worth one point.

A. Retrieval
B. Fluency
C. Response Completeness
D. Groundedness
E. Coherence

Question 2

You have a factory that contains a production line.
You need to develop a solution that will analyze a video feed to detect and track the movement of employees as they work on the production line.
Which service should you include in the solution?

A. Azure AI Face
B. Azure AI Video Indexer
C. Azure Vision in Foundry Tools Image Analysis
D. Azure Vision in Foundry Tools Spatial Analysis

Question 3

You have a customer support agent built by using the Microsoft Foundry Agent Service. The agent calls an Azure OpenAI model deployment.
During load testing, calls intermittently fail and return an HTTP 429 rate limit exceeded error.
You need to handle throttling to reduce call failures and improve reliability under load. The solution must remain within the service and model limits.
What should you do?

A. Create a new thread and retry the calls immediately.
B. Spit uploaded content into smaller files.
C. Implement a retry policy that uses exponential backoff and jitter.
D. Reduce the number of registered tools.

Question 4

A multimodal agent processes user-uploaded images. An attacker embeds hidden text instructions inside an image, hoping the agent will read and act on them. Which Azure AI Content Safety capability is designed to detect this kind of attack?

A. A content filter set to High severity for the Violence category
B. Raising the image resolution threshold on the analyser
C. Disabling the agent's file search tool
D. Prompt Shields, which detects document and indirect prompt injection

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

Solutions: