AI-3026: Develop AI agents on Azure

Kód kurzu: NP1686

Tato část není lokalizována

This intermediate-level learning path introduces AI engineers to the development of intelligent agents using Azure AI Foundry Agent Service and Semantic Kernel. Learners will explore agent architecture, tool integration, multi-agent orchestration, and secure communication protocols. The course prepares participants to build scalable, collaborative AI agents on Azure.

Odborní
certifikovaní lektoři

Mezinárodně
uznávané certifikace

Široká nabídka technických
a soft skills kurzů

Skvělý zákaznický
servis

Přizpůsobení kurzů
přesně na míru

Termíny kurzu

Počáteční datum: Na vyžádání

Garantovaný

Forma: Self-paced

Délka kurzu: 8 hodin

Jazyk: en

Cena bez DPH: 6 950 Kč

Registrovat

Počáteční datum: Na vyžádání

Garantovaný

Forma: Self-paced

Délka kurzu: 8 hodin

Jazyk: en

Cena bez DPH: 1 830 Kč

Registrovat

Počáteční
datum
Místo
konání
Forma Délka
kurzu
Jazyk Cena bez DPH
G Na vyžádání Self-paced 8 hodin en 6 950 Kč Registrovat
G Na vyžádání Self-paced 8 hodin en 1 830 Kč Registrovat
G Garantovaný kurz

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Popis kurzu

Tato část není lokalizována

Develop AI Agents

Create and deploy intelligent agents on Azure platform.

Extend with Custom Tools

Use MCP and custom tools to enhance agent capabilities.

Build Multi-Agent Systems

Leverage Semantic Kernel for agent collaboration and orchestration.

Secure & Monitor Agents

Enable discovery, secure workflows, and monitor performance.

Struktura kurzu

Tato část není lokalizována

Module 1: Get started with AI agent development on Azure

  • 1.1.1 Introduction
  • 1.2 What are AI agents?
  • 1.3 Options for agent development
  • 1.4 Microsoft Foundry Agent Service
  • 1.5 Summary

Module 2: Develop an AI agent with Microsoft Foundry Agent Service

  • 2.1 Introduction
  • 2.2 What is an AI agent
  • 2.3 How to use Microsoft Foundry Agent Service
  • 2.4 Develop agents with the Microsoft Foundry Agent Service
  • 2.5 Summary

Module 3: Develop AI agents with the Microsoft Foundry extension in Visual Studio Code

  • 3.1 Introduction
  • 3.2 Get started with the Microsoft Foundry extension
  • 3.3 Part 1 Develop AI agents in Visual Studio Code
  • 3.3 Part 2 Develop AI agents in Visual Studio Code
  • 3.4 Extend AI agent capabilities with tools
  • 3.5 Summary

Module 4: Integrate custom tools into your agent

  • 4.1 Introduction
  • 4.2 Why use custom tools
  • 4.3 Options for implementing custom tools
  • 4.4 How to integrate custom tools
  • 4.5 Summary

Module 5: Develop a multi-agent solution with Microsoft Foundry Agent Service

  • 5.1 Introduction
  • 5.2 Understand connected agents
  • 5.3 Design a multi-agent solution with connected agents
  • 5.4 Summary

Module 6: Integrate MCP Tools with Azure AI Agents

  • 6.1 Introduction
  • 6.2 Understand MCP tool discovery
  • 6.3 Integrate agent tools using an MCP server and client
  • 6.4 Use Azure AI agents with MCP servers
  • 6.5 Summary

Module 7: Develop an AI agent with Microsoft Agent Framework

  • 7.1 Introduction
  • 7.2 Understand Microsoft Agent Framework AI agents
  • 7.3 Create an Azure AI agent with Microsoft Agent Framework
  • 7.4 Add tools to Azure AI agent
  • 7.5 Summary

Module 8: Orchestrate a multi-agent solution using the Microsoft Agent Framework

  • 8.1 Introduction
  • 8.2 Understand the Microsoft Agent Framework
  • 8.3 Understand agent orchestration
  • 8.4 Use concurrent orchestration
  • 8.5 Use sequential orchestration
  • 8.6 Use group chat orchestration
  • 8.7 Use handoff orchestration
  • 8.8 Use Magentic orchestration
  • 8.9 Summary

Module 9: Discover Azure AI Agents with A2A

  • 9.1 Introduction
  • 9.2 Define an A2A agent
  • 9.3 Implement an agent executor
  • 9.4 Host an A2A server
  • 9.5 Connect to your A2A agent
  • 9.6 Summary

Module 10: Build agent-driven workflows using Microsoft Foundry

  • 10.1 Introduction
  • 10.2 Understand Workflows
  • 10.3 Identify Workflow Patterns
  • 10.4 Create workflows in Microsoft Foundry
  • 10.5 Add Agents to a Workflow
  • 10.6 Apply Power Fx in Workflows
  • 10.7 Maintain Workflows in Microsoft Foundry
  • 10.8 Use workflows in code
  • 10.9 Summary

Module 11: Build knowledge-enhanced AI agents with Foundry IQ

  • 11.1 Introduction
  • 11.2 Understanding RAG for agents
  • 11.3 Explore Foundry IQ
  • 11.4 Part 1 Configure data sources for knowledge bases
  • 11.4 Part 2 Configure data sources for knowledge bases
  • 11.5 Configure retrieval with Foundry IQ
  • 11.6 Summary

Předpokládané znalosti

Tato část není lokalizována

  • Familiarity with Azure AI services
  • Understanding of basic AI and ML concepts
  • Experience with programming and APIs
  • Completion of “Get started with AI” learning path recommended

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