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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a web app named App1 that processes user prompts by integrating with a Microsoft Foundry project named Project1. App1 performs the following actions:
- Sends prompts directly to a model by using the Azure OpenAI Responses API
- Invokes the Azure AI Content Safety tool by using a Foundry
connection within the same request
You need to configure end-to-end visibility into each step of the request workflow.
What should you do?

A) Enable logging by using Foundry Local.
B) Route requests through the Azure OpenAI endpoint.
C) Enable logging by using the client SDK for Content Safety.
D) Enable application tracing in Project1.

2. You are defining an agent in Microsoft Foundry Agent Service. The agent uses a catalogue model for reasoning, a system instruction that sets its goals, and a file search capability that reads a knowledge store. Which three components does this combination represent?

A) Embedding, retriever, generator
B) Endpoint, API key, deployment name
C) Model, instructions, tools
D) Trigger, action, condition

3. You have an application that uses a prebuilt Azure Language model.
You need to generate a summary that meets the following requirements:
- Identify each presenter in the video and attribute each text file to
sentences
- Preserves the original sentence order
- Returns exactly three sentences
Which Language service feature should you use?

A) abstractive summarization
B) sentiment analysis
C) extractive summarization
D) key phrase extraction

4. A legal team must extract clauses and inferred fields from unstructured contracts. One required field is the contract end date, which is not stated explicitly and must be derived from the start date plus the term. The team has no labelled training data. Which tool best fits?

A) An Azure AI Document Intelligence custom model trained on labelled samples
B) Azure Content Understanding using a prebuilt-contract or zero-shot custom analyser
C) The Azure AI Search semantic ranker
D) Azure Translator in Foundry Tools

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

Solutions: