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Overview
This course provides a comprehensive and practical introduction to developing intelligent AI agents on Microsoft Azure using Azure AI Foundry, Microsoft Foundry Agent Service, and the Microsoft Agent Framework. Learners will explore how AI agents represent the next generation of intelligent applications, enabling scalable, interactive, and autonomous solutions that can reason, act, and collaborate.
The course focuses on designing, building, extending, and orchestrating AI agents using Azure-native tools and developer workflows. Participants will gain hands-on experience developing single-agent and multi-agent solutions, integrating built-in and custom tools, and enabling agent discovery and communication using modern protocols. By the end of the course, learners will be equipped to design production-ready AI agents that can be applied to real-world business and technical scenarios.
Prerequisites
Participants should have:
- A basic understanding of programming concepts, such as functions, APIs, and data structures
- Familiarity with cloud computing concepts and Microsoft Azure fundamentals
- An interest in building intelligent, AI-driven applications using modern development tools
Prior experience with Azure services or AI workloads is helpful but not mandatory.
Target audience
This course is designed for:
- Developers building intelligent applications on Microsoft Azure
- Data scientists and machine learning practitioners extending solutions with AI agents
- IT professionals and solution architects designing scalable AI-driven systems
- Engineers seeking to adopt agent-based patterns for automation, orchestration, and collaboration
It is ideal for individuals looking to enhance their skills in creating interactive and extensible AI agents for business or personal projects.
Learning Objectives
By the end of this course, learners will be able to:
- Explain what AI agents are and how they are used within modern intelligent applications
- Develop AI agents using Microsoft Foundry Agent Service and Azure AI Foundry
- Build, test, and deploy AI agents using the Microsoft Foundry extension in Visual Studio Code
- Extend AI agents with built-in, custom, and MCP-hosted tools
- Design and implement multi-agent solutions using connected and orchestrated agents
- Use the Microsoft Agent Framework to create, extend, and orchestrate Azure AI agents
- Enable agent discovery and communication using the A2A protocol
Course Outline
Get started with AI agent development on Azure
This module introduces AI agents as a core building block for next-generation applications on Microsoft Azure.
- Introduction to AI agents and intelligent applications
- What AI agents are and how they differ from traditional applications
- Options for AI agent development on Azure
- Overview of Microsoft Foundry Agent Service
- Exercise exploring AI agent development concepts and tools
- Module assessment and summary
Develop an AI agent with Microsoft Foundry Agent Service
This module provides hands-on guidance for building AI agents using Microsoft Foundry Agent Service.
- Introduction to agent development with Foundry
- Understanding AI agent capabilities and behaviours
- Using Microsoft Foundry Agent Service to create agents
- Developing and configuring agents for real-world use cases
- Exercise building an AI agent with Foundry Agent Service
- Module assessment and summary
Develop AI agents with the Microsoft Foundry extension in Visual Studio Code
This module focuses on developer workflows for building and managing AI agents in Visual Studio Code.
- Introduction to the Microsoft Foundry extension
- Getting started with agent development in Visual Studio Code
- Developing and testing AI agents locally
- Extending agent capabilities with integrated tools
- Exercise building an AI agent using the Foundry extension
- Module assessment and summary
Integrate custom tools into your agent
This module explores how to extend AI agents beyond built-in functionality using custom tools.
- Introduction to agent extensibility
- Why and when to use custom tools
- Options for implementing custom tools for AI agents
- Integrating custom tools into agent workflows
- Exercise building an AI agent with custom tools
- Module assessment and summary
Develop a multi-agent solution with Microsoft Foundry Agent Service
This module introduces connected agents and collaborative AI patterns.
- Introduction to multi-agent solutions
- Understanding connected agents and agent collaboration
- Designing a multi-agent solution using Foundry Agent Service
- Exercise developing a multi-agent application with Foundry
- Module assessment and summary
Integrate MCP tools with Azure AI agents
This module enables dynamic tool access by integrating MCP-hosted tools into AI agents.
- Introduction to MCP tools and dynamic tool access
- Understanding MCP tool discovery
- Integrating agent tools using MCP servers and clients
- Using Azure AI agents with MCP servers
- Exercise connecting MCP tools to Azure AI agents
- Module assessment and summary
Develop an AI agent with Microsoft Agent Framework
This module introduces the Microsoft Agent Framework SDK for building Azure AI agents.
- Introduction to Microsoft Agent Framework
- Understanding AI agents built with the framework
- Creating an Azure AI agent using Microsoft Agent Framework
- Adding tools to Azure AI agents
- Exercise developing an Azure AI agent with the Agent Framework SDK
- Knowledge check and summary
Orchestrate a multi-agent solution using the Microsoft Agent Framework
This module focuses on coordinating multiple agents using orchestration patterns.
- Introduction to agent orchestration
- Understanding orchestration concepts in the Agent Framework
- Using concurrent orchestration
- Using sequential orchestration
- Using group chat orchestration
- Using handoff orchestration
- Using Magentic orchestration
- Exercise developing a multi-agent solution
- Knowledge check and summary
Discover Azure AI agents with A2A
This module introduces the A2A protocol for agent discovery and communication.
- Introduction to A2A and remote agent collaboration
- Defining an A2A agent
- Implementing an agent executor
- Hosting an A2A server
- Connecting to an A2A agent
- Exercise connecting to remote Azure AI agents using A2A
- Module assessment and summary
Exams and assessments
This course includes module-level assessments and knowledge checks to reinforce learning throughout the programme. There are no formal certification exams associated with this course. Practical exercises and assessments are used to validate understanding of AI agent development concepts and tools.
Hands-on learning
This course includes extensive hands-on learning through guided exercises and practical labs. Learners will build single-agent and multi-agent solutions, integrate tools, and deploy agents using Azure services and developer tooling. Instructors guide participants through real-world scenarios that reinforce practical application and problem-solving skills.
Frequently asked questions
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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course.
Once you have purchased the Online course and have completed your registration, you will receive the necessary details to enable you to immediately access it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.
All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.
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When will I receive my certificate?
Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.