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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You are building an app by using the Semantic Kernel.
You need to include complex objects in the prompt templates of the app. The solution must support objects that contain subproperties.
Which two prompt templates can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A) Liquid
B) Handlebars
C) Semantic Kernel
D) JSONL
E) YAML

2. You have a Microsoft Foundry project that contains an agent for a customer support chat app.
The agent uses a memory store and a memory search tool.
You need to ensure that the conversation history does NOT persist across separate sessions.
To what should you set the scope of the memory tool?

A) {{$userId}}
B) session
C) {{$conversationId}}
D) global

3. You are building an image sharing app that will use Azure AI to prevent users from sharing sexually explicit images.
You need to ensure that inappropriate images are identified correctly. The solution must minimize development effort.
What should you use?

A) Vision Studio in Azure AI Vision
B) Azure AI Studio
C) Azure AI Content Safety Studio
D) Visual Studio

4. You have a Microsoft Foundry project named Project1 that contains the following:
- An OpenAPI tool that calls an external API
- A project connection named Connection1 that stores the API key of the external API When an agent calls the OpenAPI tool, the API returns a 401 unauthorized error, and traces show that the API key header is NOT being sent.
You need to ensure that the OpenAPI tool automatically includes the API key from Connection1 on all requests.
What should you do?

A) Enable identity passthrough so that the tool uses the Microsoft Entra token of the caller.
B) Connect the tool to Connection1.
C) Configure the tool to use the default connection of Project1.
D) Add the API key header manually to the OpenAPI specification.

5. You have a Microsoft Foundry project.
You plan to build a customer support solution that contains an agent. The solution must meet the following requirements:
- Provide accurate, context-aware responses grounded in internal
product documentation stored in Azure AI Search.
- Require deep, multi-step reasoning across long contexts.
- Generate detailed natural language responses.
Which type of model should you use to power the agent?

A) a multimodal model
B) a large language model (LLM)
C) a key phrase extraction model
D) a small language model (SLM)

Solutions: