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Microsoft AI-103 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and manage Azure AI solutions | 25–30% | - Design Azure AI infrastructure
|
| Topic 2: Implement generative AI and agentic solutions | 30–35% | - Build generative AI applications
|
| Topic 3: Implement information extraction and knowledge mining | 10–15% | - Extract structured data from documents
|
| Topic 4: Implement computer vision solutions | 10–15% | - Build multimodal solutions
|
| Topic 5: Implement text and speech analysis solutions | 10–15% | - Implement natural language processing
|
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
You have an Azure subscription.
You plan to build an app that will use the Azure AI DALL-E model.
You need to deploy the model.
What should you use?
- A. the Azure SDK for Python and PowerShell cmdlets.
- B. the Azure portal and Microsoft Graph API
- C. Microsoft Foundry and the Azure Command Line Interface (CLI)
- D. the Azure SDK for JavaScript and Azure Machine Learning Studio.
Correct Answer: C 🗳️
Explanation: Only visible for TestInsides members. You can sign-up / login (it's free).
Hotspot Question
You have a Python application named App1 that integrates with a Microsoft Foundry project named Project1.
You need to ensure that App1 meets the following requirements:
- Authenticates by using a Microsoft Entra managed identity
- Sends prompts to a deployed model by using the Azure OpenAI Responses API 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.
Correct Answer:
You have a Microsoft Foundry project that contains an agent.
The agent uses Azure AI Search as the retriever.
You plan to ingest PDF into an Azure AI Search index to ensure that the agent can ground responses in texts in both documents and embedded images.
Users require citations that link to the source files.
You need to ensure that during indexing, the images are extracted into a structure that can be used as input for the built-in optical character recognition (OCR) skill.
Which indexing approach should you use?
- A. an indexer to extract image data into a normalized_images collection
- B. a Shaper skill to restructure the OCR input
- C. a skillset to run the OCR skill directly against the content field of the index
- D. the outputFieldMappings parameter to write image data to a searchable field
Correct Answer: A 🗳️
Explanation: Only visible for TestInsides members. You can sign-up / login (it's free).
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-read
- B. prebuilt-layout
- C. prebuilt-documentFieldSchema
- D. prebuilt-documentSearch
Correct Answer: D 🗳️
Explanation: Only visible for TestInsides members. You can sign-up / login (it's free).
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. Create a Microsoft Foundry project.
- C. Add Agent1 to the Microsoft Foundry playground.
- D. Provision an Application Insights resource.
Correct Answer: B 🗳️
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