AI-102T00 Develop AI solutions in Azure

Dieses Training richtet sich an Softwareentwickler:innen, die KI-basierte Anwendungen entwickeln möchten und dazu die Azure KI Services, Azure KI-Suche und Azure OpenAI nutzen. In diesem Kurs wird C# oder Python als Programmiersprache verwendet.
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Nehmen Sie an einem unserer Standorte Frankfurt, München und Wien oder virtuell an unseren Klassenraumtrainings teil. Unter “Termin buchen” werden Ihnen alle Optionen angezeigt, zuerst sortiert nach Standort, dann nach Datum.

Dieser Kurs wurde für Softwareingenieure entwickelt, die sich mit dem Erstellen, Verwalten und Bereitstellen von KI-Lösungen befassen, die Azure AI Foundry und andere Azure AI-Dienste nutzen. 
Sie sind mit C# oder Python vertraut und verfügen über Kenntnisse in der Verwendung REST-basierter APIs und SDKs, um generative KI, Computer vision, Sprachanalyse und Informationsextraktionslösungen in Azure zu erstellen.

Wichtige Information

Dieses Training behandelt prüfungsrelevante Themen zum Examen: Microsoft Certified: Azure AI Engineer Associate

Was werden Sie in diesem Training erlernen?

  • KI-gestützte Anwendungsentwicklung beschreiben
  • Azure Cognitive Services erstellen, konfigurieren, einsetzen und absichern
  • Anwendungen zur Textanalyse und Sprachverarbeitung entwickeln
  • Sprachgesteuerte Anwendungen entwickeln
  • Anwendungen mit Funktionen zum Verstehen natürlicher Sprache erstellen
  • QnA-Lösungen mit Azure AI Language erstellen
  • Konversationslösungen mit dem Microsoft Bot Framework entwickeln
  • Bildverarbeitungsdienste zur Analyse von Bildern und Videos nutzen
  • Benutzerdefinierte Computer-Vision-Modelle erstellen
  • Anwendungen zur Gesichtserkennung und -analyse entwickeln
  • Anwendungen entwickeln, die Text in Bildern und Dokumenten lesen und verarbeiten
  • Intelligente Suchlösungen mit Azure Cognitive Search erstellen

Agenda

Create an image classification client application
Develop an AI agent with Microsoft Agent Framework
Understand Microsoft Agent Framework AI agents
Create an Azure AI agent with Microsoft Agent Framework
Add tools to Azure AI agent
Develop an Azure AI agent with the Microsoft Agent Framework SDK
Integrate MCP Tools with Azure AI Agents
Understand MCP tool discovery
Integrate agent tools using an MCP server and client
Use Azure AI agents with MCP servers
Connect MCP tools to Azure AI Agents
Develop a multi-agent solution with Microsoft Foundry Agent Service
Understand connected agents
Design a multi-agent solution with connected agents
Develop a multi-agent app with Microsoft Foundry
Integrate custom tools into your agent
Why use custom tools
Options for implementing custom tools
How to integrate custom tools
Build an agent with custom tools
Develop AI agents with the Microsoft Foundry extension in Visual Studio Code
Get started with the Microsoft Foundry extension
Develop AI agents in Visual Studio Code
Extend AI agent capabilities with tools
Build an AI agent using the Microsoft Foundry extension
Develop an AI agent with Microsoft Foundry Agent Service
What is an AI agent
How to use Microsoft Foundry Agent Service
Develop agents with the Microsoft Foundry Agent Service
Build an AI agent
Orchestrate a multi-agent solution using the Microsoft Agent Framework
Understand the Microsoft Agent Framework
Understand agent orchestration
Use concurrent orchestration
Use sequential orchestration
Use group chat orchestration
Use handoff orchestration
Use Magentic orchestration
Develop a multi-agent solution
Get started with AI agent development on Azure
What are AI agents?
Options for agent development
Microsoft Foundry Agent Service
Explore AI Agent development
Implement a responsible generative AI solution in Microsoft Foundry
Plan a responsible generative AI solution
Map potential harms
Measure potential harms
Mitigate potential harms
Manage a responsible generative AI solution
Apply content filters to prevent the output of harmful content
Fine-tune a language model with Microsoft Foundry
Understand when to fine-tune a language model
Prepare your data to fine-tune a chat completion model
Explore fine-tuning language models in Microsoft Foundry portal
Fine-tune a language model
Develop a RAG-based solution with your own data using Microsoft Foundry
Understand how to ground your language model
Make your data searchable
Create a RAG-based client application
Implement RAG in a prompt flow
Create a generative AI app that uses your own data
Get started with prompt flow to develop language model apps in the Microsoft Foundry
Understand the development lifecycle of a large language model (LLM) app
Understand core components and explore flow types
Explore connections and runtimes
Explore variants and monitoring options
Get started with prompt flow
Develop an AI app with the Microsoft Foundry SDK
What is the Microsoft Foundry SDK?
Work with project connections
Create a chat client
Create a generative AI chat app
Choose and deploy models from the model catalog in Microsoft Foundry portal
Explore the model catalog
Deploy a model to an endpoint
Optimize model performance
Explore, deploy, and chat with language models
Evaluate generative AI performance in Microsoft Foundry portal
Assess the model performance
Manually evaluate the performance of a model
Automated evaluations
Evaluate generative AI model performance
Discover Azure AI Agents with A2A
Define an A2A agent
Implement an agent executor
Host an A2A server
Connect to your A2A agent
Connect to remote Azure AI Agents with the A2A protocol
Analyze text with Azure Language
Provision an Azure Language resource
Detect language
Extract key phrases
Analyze sentiment
Extract entities
Extract linked entities
Analyze text
Create question answering solutions with Azure Language
Understand question answering
Compare question answering to Azure Language understanding
Create a knowledge base
Implement multi-turn conversation
Test and publish a knowledge base
Use a knowledge base
Improve question answering performance
Create a question answering solution
3 min
Train an image classification model
5 min
Classify images
Azure AI Custom Vision
Detect, analyze, and recognize faces
Plan a face detection, analysis, or recognition solution
Detect and analyze faces
Verify and identify faces
Responsible AI considerations for face-based solutions
Detect and analyze faces
Read text in images
Explore Azure AI options for reading text
Read text with Azure Vision Image Analysis
Read text in images
Analyze images
Provision an Azure Vision resource
Analyze an image
Analyze images
Develop an Azure AI Voice Live agent
Explore the Azure Voice Live API
Explore the AI Voice Live client library for Python
Develop an Azure AI Voice Live agent
Develop an audio-enabled generative AI application
Deploy a multimodal model
Develop an audio-based chat app
Develop an audio-enabled chat app
Translate speech with the Azure Speech service
Provision an Azure resource for speech translation
Translate speech to text
Synthesize translations
Translate speech
Create speech-enabled apps with Microsoft Foundry
Provision an Azure resource for speech
Use the Azure Speech to Text API
Use the text to speech API
Configure audio format and voices
Use Speech Synthesis Markup Language
Create a speech-enabled app
Translate text with Azure Translator service
Provision an Azure Translator resource
Understand language detection, translation, and transliteration
Specify translation options
Define custom translations
Translate text with the Azure Translator service
Custom named entity recognition
Understand custom named entity recognition
Label your data
Train and evaluate your model
Extract custom entities
Create custom text classification solutions
Understand types of classification projects
Understand how to build text classification projects
Classify text
Build a conversational language understanding model
Understand prebuilt capabilities of the Azure Language service
Understand resources for building a conversational language understanding model
Define intents, utterances, and entities
Use patterns to differentiate similar utterances
Use pre-built entity components
Train, test, publish, and review a conversational language understanding model
Build a conversational language understanding model
3 minClassify images
Plan and prepare to develop AI solutions on Azure
What is AI?
Foundry Tools
Microsoft Foundry
Developer tools and SDKs
Responsible AI
Prepare for an AI development project
  • Group Exercise: Review Architecting on AWS core best practices
  • Lab 1: Securing Amazon S3 VPC Endpoint Communications
  • Group Exercise: Review Architecting on AWS core best practices
  • AWS Organizations for multi-account access and permissions
  • AWS SSO to simplify access and authentication across AWS accounts and third-party services
  • AWS Control Tower
  • Permissions, access, and authentication
  • Group Exercise: Review Architecting on AWS core best practices
  • Lab 1: Securing Amazon S3 VPC Endpoint Communications
  • Group Exercise: Review Architecting on AWS core best practices
  • Lab 1: Securing Amazon S3 VPC Endpoint Communications

Dein Training im Überblick

Dauer 5 Tage
Trainingssprache Deutsch
Trainingsart brainyCLASS (offen)

2.980,00 €

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