Microsoft AI-103 Q&A - in .pdf

  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Sep 04, 2026
  • Q & A: 159 Questions and Answers
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Microsoft AI-103 Q&A - Testing Engine

  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Sep 04, 2026
  • Q & A: 159 Questions and Answers
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Microsoft AI-103 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement information extraction and knowledge mining10–15%- Extract structured data from documents
  • 1. Process forms, invoices, and unstructured content
  • 2. Use Azure AI Document Intelligence
- Build knowledge bases and search solutions
  • 1. Design knowledge mining pipelines
  • 2. Implement Azure AI Search
  • 3. Create and manage vector indexes
Topic 2: Plan and manage Azure AI solutions25–30%- Manage AI solution development lifecycle
  • 1. Integrate with CI/CD pipelines
  • 2. Monitor and maintain AI workloads
  • 3. Configure model and agent deployments
- Design Azure AI infrastructure
  • 1. Plan for security, compliance, and responsible AI
  • 2. Design for scalability, availability, and cost optimization
  • 3. Select appropriate Azure AI Foundry services
Topic 3: Implement generative AI and agentic solutions30–35%- Design and implement intelligent agents
  • 1. Select agent architecture patterns
  • 2. Integrate agents with external systems and data sources
  • 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 function calling and tool use
  • 4. Implement prompt engineering and optimization
Topic 4: Implement computer vision solutions10–15%- Implement image analysis and processing
  • 1. Use Azure AI Vision services
  • 2. Extract text and structure from images
  • 3. Implement object detection and image classification
- Build multimodal solutions
  • 1. Process and analyze video content
  • 2. Combine vision and language capabilities
Topic 5: 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. Build conversational language understanding
  • 2. Perform sentiment analysis, entity recognition, and summarization
  • 3. Use Azure AI Language services

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question 1

A team wants to deploy a model from the Foundry catalogue with the fastest possible setup, pay only for the tokens they consume, and avoid provisioning any virtual machine (VM) quota. Which deployment option fits?

A. Self-hosted deployment on Azure Kubernetes Service
B. Managed compute (managed endpoint) deployment
C. A local container running on a developer workstation
D. Serverless API deployment, also called models as a service (MaaS)


Question 2

You are creating an image-editing workflow in a Microsoft Foundry project.
The workflow must meet the following requirements:
- Ensure that background objects can be removed by applying a mask-
based inpainting edit.
- Preserve the original lighting and style of the edited images.
- Use the built-in image editing controls, NOT a custom model.
You need to ensure that image edits apply exclusively inside the masked area.
How should you configure the workflow?

A. Enable image_to_image mode and a high-strength value to regenerate the full image based on the prompt.
B. Enable mask_inpainting and supply both the input image and a mask indicating which part of the image to modify.
C. Enable text_to_image mode and a prompt describing the desired background removal.
D. Set generation mode to image_variation and provide the original image as a reference.


Question 3

You are building a chatbot.
You need to ensure that the chatbot can classify user input into separate categories. The categories must be dynamic and defined at the time of inference.
Which service should you use to classify the input?

A. Azure OpenAI text summarization
B. Azure OpenAI text classification
C. Azure AI Language custom named entity recognition (NER)
D. Azure AI Language custom text classification


Question 4

You build a chatbot that uses the Azure OpenAI GPT-4 model to generate song lyrics.
You need to ensure that responses do NOT contain lyrics from popular songs that might have been ingested during model training.
Which Azure AI Content Safety API should you use?

A. Protected material text detection
B. Custom categories
C. Groundedness detection
D. Analyze Text


Question 5

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. Azure AI Content Safety Studio
B. Vision Studio in Azure AI Vision
C. Azure AI Studio
D. Visual Studio


Solutions:

Question 1
Answer: D
Question 2
Answer: B
Question 3
Answer: B
Question 4
Answer: A
Question 5
Answer: A

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