Microsoft AI-103 Q&A - in .pdf

  • AI-103 pdf
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Jul 28, 2026
  • Q & A: 159 Questions and Answers
  • Convenient, easy to study.
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  • PDF Price: $59.98

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  • Exam Name: Developing AI Apps and Agents on Azure
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  • Updated: Jul 28, 2026
  • Q & A: 159 Questions and Answers
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Microsoft AI-103 Q&A - Testing Engine

  • AI-103 Testing Engine
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Jul 28, 2026
  • Q & A: 159 Questions and Answers
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Microsoft AI-103 Exam Syllabus Topics:

SectionWeightObjectives
Implement text and speech analysis solutions10–15%- Implement speech capabilities
  • 1. Speech-to-text and text-to-speech integration
  • 2. Speech translation and speaker recognition
- Implement natural language processing
  • 1. Use Azure AI Language services
  • 2. Build conversational language understanding
  • 3. Perform sentiment analysis, entity recognition, and summarization
Implement information extraction and knowledge mining10–15%- Build knowledge bases and search solutions
  • 1. Implement Azure AI Search
  • 2. Design knowledge mining pipelines
  • 3. Create and manage vector indexes
- Extract structured data from documents
  • 1. Process forms, invoices, and unstructured content
  • 2. Use Azure AI Document Intelligence
Implement generative AI and agentic solutions30–35%- Design and implement intelligent agents
  • 1. Integrate agents with external systems and data sources
  • 2. Select agent architecture patterns
  • 3. Manage state, memory, and context
  • 4. Implement multi-agent workflows and orchestration
- Build generative AI applications
  • 1. Integrate Azure OpenAI and other models
  • 2. Build retrieval-augmented generation (RAG) solutions
  • 3. Implement prompt engineering and optimization
  • 4. Implement function calling and tool use
Plan and manage Azure AI solutions25–30%- Design Azure AI infrastructure
  • 1. Plan for security, compliance, and responsible AI
  • 2. Select appropriate Azure AI Foundry services
  • 3. Design for scalability, availability, and cost optimization
- Manage AI solution development lifecycle
  • 1. Monitor and maintain AI workloads
  • 2. Configure model and agent deployments
  • 3. Integrate with CI/CD pipelines
Implement computer vision solutions10–15%- Implement image analysis and processing
  • 1. Implement object detection and image classification
  • 2. Use Azure AI Vision services
  • 3. Extract text and structure from images
- Build multimodal solutions
  • 1. Process and analyze video content
  • 2. Combine vision and language capabilities

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. 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) Create a Microsoft Foundry project.
B) Add Agent1 to the Microsoft Foundry playground.
C) Add Agent1to a Microsoft Foundry project.
D) Provision an Application Insights resource.


2. In Azure AI Studio, you use Completions playground with the GPT-35 Turbo model.
You have a prompt that contains the following code.
function F(n)
{
var f = [0, 1];
for (var i = 2; i < n; i++) f[i] = f[i-1] + f[i-2];
return f;
}
You need the model to create an explanation of the code. The solution must minimize costs.
What should you do?

A) Add function F(explanation) to the prompt.
B) Set the temperature parameter to 1.
C) Add // what does function F do? to the prompt.
D) Change the model to GPT-4-32k.


3. You have a Microsoft Foundry project that contains an agent.
You need to process mixed-format documents that contain scanned text, tables, and multicolumn layouts. The extracted content must preserve the document structure and be converted into the Markdown format for downstream reasoning.
What should you configure first?

A) an Azure Language in Foundry Tools text analysis model deployment
B) an Azure Content Understanding in Foundry Tools analyzer
C) a generative chat completion request
D) an Azure OpenAI Responses API call that uses a multimodal model


4. You have a Microsoft Foundry project that contains an agent and uses a GitHub repository. The repository contains a YAM file named File1 that defines the evaluation settings of the agent. You need to create a GitHub Actions workflow that runs the evaluation defined in File1 when a pull request (PR) is opened. How should you configure the workflow?

A) Set model-deployment-name to the deployed model.
B) Set project-endpoint to the endpoint of the project.
C) Set tenant-id to the Microsoft Entra tenant ID
D) Set evaluation-config to the path of the YAML file.


5. Drag and Drop Question
You have a Microsoft Foundry project that contains an agent used by the financial analysts at your company.
You need to optimize the agent workflow by providing additional data access and processing capabilities. The solution must meet the following requirements:
- Ensure that the agent can perform calculations during conversations.
- Ensure that the agent can access up-to-date information from public
websites.
- Ensure that the agent can retrieve information from documents
uploaded directly to the agent.
What should you use for each requirement? To answer, drag the appropriate tools to the correct requirements. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: C
Question # 3
Answer: B
Question # 4
Answer: B
Question # 5
Answer: Only visible for members

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