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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 that contains a model deployment.
You have an application that calls the deployment by using the Azure OpenAI v1 API and DefaultAzureCredential.
The developers at your company receive HTTP 403 errors when they send inference requests, even after running az login.
You need to ensure that the developers can perform model inference. The solution must follow the principle of least privilege.
Which role-based access control (RBAC) role should you assign to the developers?

A) Cognitive Services User
B) Cognitive Services Data Reader
C) Cognitive Services OpenAI User
D) Contributor

2. You have a Microsoft Foundry project that contains an agent.
The agent uses Azure Content Understanding in Foundry Too to process vendor onboarding packets. The packs include digital PDFs that contain tables and hyperlinks.
The extracted content is indexed for search and provided to a downstream agent in the Markdown format.
You need to generate a Markdown output that has a layout and a semantic structure optimized for Retrieval Augmented Generation (RAG) workflows.
Which built-in analyzer should you use?

A) prebuilt-layout
B) prebuilt-documentSearch
C) prebuilt-documentFieldSchema
D) prebuilt-read

3. You have a Microsoft Foundry project that contains a customer support agent. The agent calls an internal knowledge API tool before generating responses.
Users report the following issues:
- Some requests take more than 15 seconds to complete.
- Some responses are incorrect, even when the knowledge API returns the expected data.
You need to inspect individual agent runs to view the ordered sequence of large language model (LLM) calls, tool invocations, and timing information.
Which observability capability should you use?

A) safety metrics
B) tracing
C) monitoring
D) token usage

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

5. You have an invoice-processing application named App1 that uses Azure Constant Understanding in Foundry Tools.
You are building a new Content Understanding pipeline named Pipeline1 that must meet the following requirements:
- Compare an invoice to its related purchase order
- Validate the voice against static vendor contact documents
- Return a single structured output that includes discrepancy findings
You need to configure Pipeline1 and expose the pipeline as a single analyzer endpoint. What should you configure?

A) a single-file task in standard mode that uses confidence scores enabled for the extracted fields.
B) a single-file task in standard mode that uses the vendor contract provided as an additional document during analysis.
C) a multi-file task in standard mode that uses the invoice and purchase order as input to the analyzer
D) a multiple-file task in pro mode that uses the vendor contract files as reference data

Solutions: