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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have an Azure subscription that contains an Azure OpenAI resource.
You plan to build an agent by using the Azure AI Agent Service. The agent will perform the following actions:
- Interpret written and spoken questions from users.
- Generate answers to the questions.
- Output the answers as speech.
You need to create the project for the agent.
What should you use?

A) Azure AI Foundry
B) Speech Studio
C) Language Studio
D) the Azure portal

2. You have an Azure AI Search indexer that ingests PDF policy manuals.
Client applications must display page-level citations that have bounding polygons for both text and images.
You need to add a single built-in multimodal content extraction skill to the Azure AI Search skillset. The solution must meet the following requirements:
- Provide text and image location metadata.
- Extract tables that span multiple pages.
What should you add?

A) Azure Content Understanding in Foundry Tools
B) Document Layout
C) Document Extraction
D) GenAI Prompt

3. You have a Semantic Kernel agent that provides answers to product questions.
You plan to extend the capabilities of the agent to answer questions about the status of orders.
You need to ensure that the agent answers order status questions as quickly as possible. The solution must minimize development effort.
What should you include in the solution?

A) a plugin
B) an agent
C) a kernel
D) a function

4. An application must translate a high volume of standard product descriptions into 20 languages quickly, consistently, and at the lowest cost. The text is straightforward, with no domain-specific nuance. Which approach best fits?

A) Azure AI Document Intelligence
B) Azure Translator in Foundry Tools
C) A separately fine-tuned model for each of the 20 target languages
D) A large language model translation flow with a custom system prompt

5. You have a Microsoft Foundry project that contains an agent. The agent has a Model Context Protocol (MCP) tool that queries a knowledge base stored in Azure AI Search.
Some agent runs return answers from the base model without invoking the knowledge base, which results in responses without grounded citations.
You are provided with the following code snippet that runs the agent.

You need to add the correct tool _choiceparameter to the code to deterministically force the agent to invoke the MCP tool on each run.
What should you add?

A) tool_choice={"type":"knowledge_base"}
B) tool_choice ={"type":"mcp"}
C) tool_choice={"required"}
D) tool_choice={"auto"}

Solutions: