Develop AI Apps and Agents on Azure (AI-103)

Course 8769

  • Duration: 4 days
  • Exam Voucher: Yes
  • Language: English
  • Level: Intermediate

This 4-day, hands-on course provides a comprehensive, end-to-end approach to building AI-powered applications and agents using Microsoft Azure and Microsoft Foundry. Participants will learn how to design, develop, and optimize generative AI solutions that incorporate text, speech, vision, and multimodal capabilities.

Starting with foundational concepts and model selection, learners progress through building chat applications, integrating tools, and optimizing model performance using techniques such as prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning. The course then expands into advanced topics including AI agents, multi-agent orchestration, and workflow automation.

Participants will also explore how to build intelligent applications that process and generate text, speech, images, and video, as well as extract insights from documents and enterprise data. By the end of the course, learners will be equipped to design scalable, responsible, and production-ready AI solutions that deliver real business value.

Develop AI Apps on Azure Training Delivery Methods

  • In-Person

  • Online

  • Upskill your whole team by bringing Private Team Training to your facility.

Develop AI Apps on Azure Training Information

  • In this course, you will:

    • Design and build end-to-end AI solutions using Microsoft Foundry and Azure
    • Select, deploy, and evaluate AI models based on performance and use case
    • Develop generative AI applications, including chat-based and tool-enabled solutions
    • Optimize AI outputs using prompt engineering, RAG, and fine-tuning techniques
    • Build and integrate AI agents, including multi-agent and workflow-driven solutions
    • Create applications that process and generate text, speech, images, and video
    • Extract insights from documents and unstructured data using AI services
    • Implement responsible AI practices, including risk mitigation and governance
    • Integrate AI solutions with enterprise platforms such as Microsoft 365

    Prerequisites:

    • Basic understanding of programming concepts (Python or similar recommended)
    • Familiarity with cloud computing concepts (preferably Microsoft Azure)
    • General understanding of APIs and application development
    • Introductory knowledge of AI concepts and terminology
    • Experience using common development tools and environments
  • Who should attend:

    • Developers building AI-powered applications
    • Software engineers looking to incorporate generative AI into solutions
    • Solution architects designing AI and cloud-based systems
    • Technical consultants implementing AI solutions for clients
    • Data professionals expanding into AI application development
    • AI/ML practitioners looking to work with Azure AI and Foundry tools

Develop AI Apps on Azure Training Outline

Plan and Prepare to Develop AI Solutions on Azure

  • Understand core AI concepts
  • Explore Microsoft Foundry and available tools
  • Identify developer tools and SDKs
  • Apply responsible AI principles
  • Prepare for an AI development project

Select, Deploy, and Evaluate Microsoft Foundry Models

  • Explore the model catalog
  • Select models using benchmarks
  • Deploy models to endpoints
  • Evaluate model performance

Develop a Generative AI Chat App with Microsoft Foundry

  • Explore models using the playground
  • Choose endpoints and SDKs
  • Generate responses with APIs
  • Build chat applications

Develop Generative AI Apps that Use Tools

  • Understand tools and their purpose
  • Use code interpreter, web search, and file search
  • Implement function-based tools
  • Build tool-enabled chat apps

Optimize Generative AI Model Performance

  • Apply prompt engineering
  • Use Retrieval Augmented Generation (RAG)
  • Fine-tune models
  • Compare optimization strategies

Implement a Responsible Generative AI Solution

  • Plan responsible AI solutions
  • Identify and measure risks
  • Mitigate harmful outputs
  • Apply guardrails and governance

Develop AI Agents with Microsoft Foundry and Visual Studio Code

  • Understand AI agents and Microsoft Foundry Agent Service
  • Explore development approaches for agent-based solutions
  • Build and configure agents in Microsoft Foundry
  • Set up and use Visual Studio Code for agent development
  • Extend agent capabilities with tools
  • Test, deploy, and integrate agents into applications

Integrate Custom Tools into Your Agent

  • Understand when and why to use custom tools
  • Explore implementation options for custom tools
  • Integrate custom tools into agent workflows
  • Extend agent functionality beyond built-in capabilities

Integrate MCP Tools with Azure AI Agents

  • Understand MCP tool discovery
  • Connect agents to MCP servers
  • Enable dynamic tool usage within agent workflows

Build Knowledge-Enhanced AI Agents with Foundry IQ

  • Apply Retrieval Augmented Generation (RAG) for agents
  • Use Foundry IQ for shared knowledge access
  • Configure data sources for knowledge bases
  • Optimize retrieval and response quality

Integrate Your Agent with Microsoft 365

  • Publish agents to Microsoft Teams and Microsoft 365 Copilot
  • Use Microsoft 365 Agents Toolkit
  • Access and utilize Microsoft 365 data with Work IQ
  • Test and refine integrated agent solutions

Build Agent-Driven Workflows Using Microsoft Foundry

  • Understand workflow concepts and patterns
  • Create and manage workflows in Microsoft Foundry
  • Integrate agents into workflows
  • Use Power Fx within workflows
  • Maintain and extend workflow-based solutions

Develop an AI Agent with Microsoft Agent Framework

  • Understand the Microsoft Agent Framework
  • Build agents using the SDK
  • Add tools and extend agent capabilities

Orchestrate a Multi-Agent Solution Using Microsoft Agent Framework

  • Understand multi-agent architectures
  • Implement orchestration patterns (concurrent, sequential, group, handoff)
  • Enable collaboration between agents

Discover Azure AI Agents with A2A

  • Understand the A2A (agent-to-agent) protocol
  • Implement agent discovery and communication
  • Build distributed agent solutions

Analyze Text with Azure Language in Foundry Tools

  • Use Azure Language capabilities in Microsoft Foundry
  • Detect language in text inputs
  • Extract entities and key information
  • Identify and redact personally identifiable information (PII)

Develop a Text Analysis Agent with the Azure Language MCP Server

  • Understand the Azure Language MCP server
  • Connect MCP services to AI agents
  • Build agents for text analysis tasks such as language detection and entity recognition

Develop a Speech-Capable Generative AI Application

  • Choose speech-capable AI models
  • Transcribe speech to text
  • Synthesize speech from text
  • Build applications with voice interaction capabilities

Create Speech-Enabled Apps with Azure Speech in Microsoft Foundry Tools

  • Use Speech-to-Text and Text-to-Speech APIs
  • Configure audio formats and voice options
  • Implement Speech Synthesis Markup Language (SSML)
  • Build applications with speech recognition and synthesis

Develop a Speech Agent with the Azure Speech MCP Server

  • Understand the Azure Speech MCP server
  • Integrate speech capabilities into AI agents
  • Build agents for speech-to-text and text-to-speech tasks

Develop an Azure Speech Voice Live Agent in Microsoft Foundry

  • Use the Azure Voice Live API and SDK
  • Build real-time conversational voice agents
  • Integrate voice capabilities into AI applications

Translate Text and Speech with Microsoft Foundry Tools

  • Use translation services in Microsoft Foundry
  • Translate text between languages
  • Translate speech in real time
  • Build multilingual AI applications

Develop a Vision-Enabled Generative AI Application

  • Use vision-capable models in Microsoft Foundry
  • Build chat applications that respond to visual inputs
  • Develop and test vision-enabled AI solutions

Generate Images with AI

  • Understand image generation models
  • Explore image generation in Microsoft Foundry
  • Build applications that generate images from natural language prompts

Generate Videos with Microsoft Foundry

  • Deploy video generation models
  • Generate videos from text prompts
  • Build applications using video generation APIs and SDKs

Analyze Images with Content Understanding

  • Understand Azure Content Understanding capabilities
  • Analyze images to extract insights and meaning
  • Build solutions for image analysis

Create a Multimodal Analysis Solution with Azure Content Understanding

  • Use Azure Content Understanding for multimodal data analysis
  • Create and configure content analyzers
  • Extract and process information from multiple data types

Create an Azure Content Understanding Client Application

  • Prepare and use Content Understanding APIs
  • Build client applications for content analysis
  • Process and analyze multimodal content programmatically

Extract Data with Azure Document Intelligence

  • Understand document processing and OCR capabilities
  • Use prebuilt models for data extraction
  • Train and implement custom models
  • Extract structured data from forms and documents

Create a Knowledge Mining Solution with Azure AI Search

  • Understand Azure AI Search capabilities
  • Extract and index data using indexers
  • Enrich data with AI skills
  • Query and search indexed data
  • Persist and manage knowledge stores

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Develop AI Apps on Azure Training FAQs

No advanced AI experience is required. A basic understanding of AI concepts and general development knowledge is helpful, but the course is designed to guide you from foundational concepts through advanced, hands-on implementation.

This is a highly hands-on course. You’ll build real AI applications, agents, and workflows using Microsoft Foundry and Azure services—not just watch demos or slides.

You’ll work with Microsoft Foundry, Azure AI services, APIs, SDKs, and development tools such as Visual Studio Code. The course also covers integrations with Microsoft 365 and enterprise data sources.

Yes. The course focuses on practical use cases, including chat applications, AI agents, multimodal solutions (text, speech, vision), and document/data processing—skills you can apply immediately in your organization.

Yes. Responsible AI is built into the course, including identifying risks, applying guardrails, and designing solutions that are secure, compliant, and aligned with best practices.