Microsoft AI-103 dumps - 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
  • PDF Price: $59.99
  • Free Demo

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  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Jul 28, 2026
  • Q & A: 159 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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Microsoft AI-103 dumps - 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
  • Software Price: $59.99
  • Testing Engine

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Microsoft AI-103 Exam Syllabus Topics:

SectionWeightObjectives
Implement computer vision solutions10-15%- Analyze visual content
  • 1. Use multimodal vision APIs
  • 2. Process images and video
  • 3. Implement OCR and visual understanding
Implement text analysis and information extraction solutions10-15%- Analyze and extract information
  • 1. Extract entities and structured data
  • 2. Implement natural language processing
  • 3. Use document intelligence services
Implement generative AI solutions25-30%- Optimize and evaluate models
  • 1. Configure content filters and safety
  • 2. Implement multimodal AI capabilities
  • 3. Evaluate responses and grounding
- Develop generative AI applications
  • 1. Use Azure OpenAI and Foundry models
  • 2. Implement prompt engineering
  • 3. Build retrieval-augmented generation solutions
Plan and manage Azure AI solutions25-30%- Plan Azure AI resources
  • 1. Configure authentication and security
  • 2. Select Azure AI services and Foundry resources
  • 3. Manage deployments and monitoring
- Manage AI solution lifecycle
  • 1. Apply responsible AI practices
  • 2. Monitor model and application performance
  • 3. Implement CI/CD for AI applications
Implement agentic solutions20-25%- Build AI agents
  • 1. Integrate tools and external knowledge
  • 2. Create autonomous and multi-agent workflows
  • 3. Configure memory and orchestration
- Manage agent operations
  • 1. Secure agent interactions
  • 2. Implement scalable deployments
  • 3. Monitor and debug agents

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

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


2. You have a Microsoft Foundry project that contains an agent. The agent uses Azure Speech in Foundry Tools.
You fine-tune a baseline speech to text model for the en-us locale and publish the model.
The agent calls the Speech to text REST API and returns an error message indicating that the project ID is invalid.
You need to set the project property to the correct ID.
To what should you set the project property?

A) the custom speech endpoint URL
B) the project ID
C) the custom speech project ID
D) the project URL


3. A customer support agent must answer from an internal knowledge base that is updated weekly with new product documentation, and its answers must always reflect the latest content. Which approach should you implement?

A) Apply Direct Preference Optimization (DPO) to the documents
B) Raise the model temperature to improve recall of recent facts
C) Fine-tune the base model on the new documents every week
D) Implement retrieval-augmented generation (RAG) over an index of the documents


4. Drag and Drop Question
You have a Microsoft Foundry project that contains an agent. The agent uses threads and file uploads and calls an Azure OpenAI model deployment.
During load testing, calls intermittently fall and return an HTTP 429 rate limit exceeded error.
Some user uploads fail and generate an HTTP 400 file size exceeded error.
You need to mitigate the errors and reduce call failures. The solution must remain within the service and model limits.
What should you do to resolve each error? To answer, drag the appropriate actions to the correct errors. Each action 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 comet selection is worth one point.


5. You are deploying a support agent that enables users to upload photos.
You need to automatically classify uploaded images for harmful content. The solution must block content based on severity levels.
What should you do?

A) Enable prompt shields.
B) Use blocklists.
C) Implement image moderation.
D) Apply keyword scanning to optical character recognition (OCR) output by using Azure Vision in Foundry Tools.


Solutions:

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

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