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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. Hotspot Question
You have a Microsoft Foundry project that contains a deployed chat model.
You have a Python service that sends API requests to the model. The service is integrated with an automated validation system that compares generated outputs against approved response patterns.
Stakeholders report that small wording differences are causing validation mismatches.
You need to update the request parameters to improve output stability. The solution must maximize reasoning quality.
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.

2. Hotspot Question
You develop a test method to verify the results retrieved from a call to the Azure Vision in Foundry Tools API. The call is used to analyze the existence of company logos in images. The call returns a collection of brands named brands.
You have the following code segment:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

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

4. You plan to configure an evaluation in Microsoft Foundry for a Retrieval Augmented Generation (RAG) chat app.
You need to provide scores for groundedness, relevance, and harmful content categories.
Which two evaluation categories can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A) similarity evaluators
B) AI quality (AI assisted) metrics
C) AI quality (NLP) metrics
D) risk and safety metrics
E) fluency evaluator

5. Hotspot Question
You have a Microsoft Foundry project that contains an agent named PaymentAgent.
PaymentAgent includes a function tool that issues customer refunds by using an external API.
You are creating a workflow in YAML.
You need to ensure that the workflow pauses for human approval and continues with the refund step only after approval is granted.
How should you complete the workflow definition? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Solutions: