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Develop AI solutions in Azure
Duration
5 Days
Course
MOC-AI-102T00-A
Available Formats
Classroom Training, Online Training
Course Description
Overview
AI-102: Develop AI solutions in Azure is intended for software developers wanting to build AI infused applications that leverage Azure AI Foundry and other Azure AI services. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement computer vision and information extraction.Objectives
Upon completion of the Plan, configure, and manage collaboration communications systems with Microsoft Teams course, students will be able to:
- Select a language model from the model catalog.
- Deploy a model to an endpoint.
- Test a model and improve the performance of the model.
- Identify the need to ground your language model with Retrieval Augmented Generation (RAG)
- Index your data with Azure AI Search to make it searchable for language models
- Build an agent using RAG on your own data in the Azure AI Foundry portal
Audience
This course was designed for software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Foundry and other Azure AI services. They are familiar with C# or Python and have knowledge on using REST-based APIs and SDKs to build generative AI, computer vision, language analysis, and information extraction solutions on Azure.
Prerequisites
-
Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. Consider completing the Get started with artificial intelligence learning path first.
Topics
- Plan and prepare to develop AI solutions on Azure
- Introduction
- What is AI?
- Azure AI services
- Azure AI Foundry
- Developer tools and SDKs
- Responsible AI
- Exercise - Prepare for an AI development project
- Module assessment
- Summary
- Choose and deploy models from the model catalog in Azure AI Foundry portal
- Introduction
- Explore the model catalog
- Deploy a model to an endpoint
- Optimize model performance
- Exercise - Explore, deploy, and chat with language models
- Module assessment
- Summary
- Develop an AI app with the Azure AI Foundry SDK
- Introduction
- What is the Azure AI Foundry SDK?
- Work with project connections
- Create a chat client
- Exercise - Create a generative AI chat app
- Module assessment
- Summary
- Get started with prompt flow to develop language model apps in the Azure AI Foundry
- Introduction
- 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
- Exercise - Get started with prompt flow
- Module assessment
- Summary
- Develop a RAG-based solution with your own data using Azure AI Foundry
- Introduction
- Understand how to ground your language model
- Make your data searchable
- Create a RAG-based client application
- Implement RAG in a prompt flow
- Exercise - Create a generative AI app that uses your own data
- Module assessment
- Summary
- Fine-tune a language model with Azure AI Foundry
- Introduction
- Understand when to fine-tune a language model
- Prepare your data to fine-tune a chat completion model
- Explore fine-tuning language models in Azure AI Foundry portal
- Exercise - Fine-tune a language model
- Module assessment
- Summary
- Implement a responsible generative AI solution in Azure AI Foundry
- Introduction
- Plan a responsible generative AI solution
- Map potential harms
- Measure potential harms
- Mitigate potential harms
- Manage a responsible generative AI solution
- Exercise - Apply content filters to prevent the output of harmful content
- Module assessment
- Summary
- Evaluate generative AI performance in Azure AI Foundry portal
- Introduction
- Assess the model performance
- Manually evaluate the performance of a model
- Automated evaluations
- Exercise - Evaluate generative AI model performance
- Module assessment
- Summary
- Get started with AI agent development on Azure
- Introduction
- What are AI agents?
- Options for agent development
- Azure AI Foundry Agent Service
- Exercise - Explore AI Agent development
- Module assessment
- Summary
- Develop an AI agent with Azure AI Foundry Agent Service
- Introduction
- What is an AI agent
- How to use Azure AI Foundry Agent Service
- Develop agents with the Azure AI Foundry Agent Service
- Exercise - Build an AI agent
- Module assessment
- Summary
- Integrate custom tools into your agent
- Introduction
- Why use custom tools
- Options for implementing custom tools
- How to integrate custom tools
- Exercise - Build an agent with custom tools
- Module assessment
- Summary
- Develop a multi-agent solution with Azure AI Foundry Agent Service
- Introduction
- Understand connected agents
- Design a multi-agent solution with connected agents
- Exercise - Develop a multi-agent app with Azure AI Foundry
- Module assessment
- Summary
- Integrate MCP Tools with Azure AI Agents
- Introduction
- Understand MCP tool discovery
- Integrate agent tools using an MCP server and client
- Use Azure AI agents with MCP servers
- Exercise - Connect MCP tools to Azure AI Agents
- Module assessment
- Summary
- Develop an AI agent with Semantic Kernel
- Introduction
- Understand Semantic Kernel AI agents
- Create an Azure AI agent with Semantic Kernel
- Add plugins to Azure AI agent
- Exercise - Develop an Azure AI agent with the Semantic Kernel SDK
- Knowledge check
- Summary
- Orchestrate a multi-agent solution using Semantic Kernel
- Introduction
- Understand the Semantic Kernel Agent Framework
- Create an agent group chat
- Design an agent selection strategy
- Define a chat termination strategy
- Exercise - Develop a multi-agent solution
- Knowledge check
- Summary
- Analyze text with Azure AI Language
- Introduction
- Provision an Azure AI Language resource
- Detect language
- Extract key phrases
- Analyze sentiment
- Extract entities
- Extract linked entities
- Exercise - Analyze text
- Module assessment
- Summary
- Create question answering solutions with Azure AI Language
- Introduction
- Understand question answering
- Compare question answering to Azure AI Language understanding
- Create a knowledge base
- Test and publish a knowledge base
- Use a knowledge base
- Improve question answering performance
- Exercise - Create a question answering solution
- Module assessment
- Summary
- Build a conversational language understanding model
- Introduction
- Understand prebuilt capabilities of the Azure AI 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
- Exercise - Build an Azure AI services conversational language understanding model
- Module assessment
- Summary
- Create a custom text classification solution
- Introduction
- Understand types of classification projects
- Understand how to build text classification projects
- Exercise - Classify text
- Module assessment
- Summary
- Custom named entity recognition
- Introduction
- Understand custom named entity recognition
- Label your data
- Train and evaluate your model
- Exercise - Extract custom entities
- Module assessment
- Summary
- Translate text with Azure AI Translator service
- Introduction
- Provision an Azure AI Translator resource
- Understand language detection, translation, and transliteration
- Specify translation options
- Define custom translations
- Exercise - Translate text with the Azure AI Translator service
- Module assessment
- Summary
- Create speech-enabled apps with Azure AI services
- Introduction
- Provision an Azure resource for speech
- Use the Azure AI Speech to Text API
- Use the text to speech API
- Configure audio format and voices
- Use Speech Synthesis Markup Language
- Exercise - Create a speech-enabled app
- Module assessment
- Summary
- Translate speech with the Azure AI Speech service
- Introduction
- Provision an Azure resource for speech translation
- Translate speech to text
- Synthesize translations
- Exercise - Translate speech
- Module assessment
- Summary
- Develop an audio-enabled generative AI application
- Introduction
- Deploy a multimodal model
- Develop an audio-based chat app
- Exercise - Develop an audio-enabled chat app
- Module assessment
- Summary
- Analyze images
- Introduction
- Provision an Azure AI Vision resource
- Analyze an image
- Exercise - Analyze images
- Module assessment
- Summary
- Read text in images
- Introduction
- Explore Azure AI options for reading text
- Read text with Azure AI Vision Image Analysis
- Exercise - Read text in images
- Module assessment
- Summary
- Detect, analyze, and recognize faces
- Introduction
- Plan a face detection, analysis, or recognition solution
- Detect and analyze faces
- Verify and identify faces
- Responsible AI considerations for face-based solutions
- Exercise - Detect and analyze faces
- Module assessment
- Summary
- Classify images
- Introduction
- Azure AI Custom Vision
- Train an image classification model
- Create an image classification client application
- Exercise - Classify images
- Module assessment
- Summary
- Detect objects in images
- Introduction
- Use Azure AI Custom Vision for object detection
- Train an object detector
- Develop an object detection client application
- Exercise - Detect objects in images
- Module assessment
- Summary
- Analyze video
- Introduction
- Understand Azure Video Indexer capabilities
- Extract custom insights
- Use Video Analyzer widgets and APIs
- Exercise - Analyze video
- Module assessment
- Summary
- Develop a vision-enabled generative AI application
- Introduction
- Deploy a multimodal model
- Develop a vision-based chat app
- Exercise - Develop a vision-enabled chat app
- Module assessment
- Summary
- Generate images with AI
- Introduction
- What are image-generation models?
- Explore image-generation models in Azure AI Foundry portal
- Create a client application that uses an image generation model
- Exercise - Generate images with AI
- Module assessment
- Summary
- Create a multimodal analysis solution with Azure AI Content Understanding
- Introduction
- What is Azure AI Content Understanding?
- Create a Content Understanding analyzer
- Use the Content Understanding REST API
- Exercise - Extract information from multimodal content
- Module assessment
- Summary
- Create an Azure AI Content Understanding client application
- Introduction
- Prepare to use the AI Content Understanding REST API
- Create a Content Understanding analyzer
- Analyze content
- Exercise - Develop a Content Understanding client application
- Module assessment
- Summary
- Use prebuilt Document intelligence models
- Introduction
- Understand prebuilt models
- Use the General Document, Read, and Layout models
- Use financial, ID, and tax models
- Exercise - Analyze a document using Azure AI Document Intelligence
- Module assessment
- Summary
- Extract data from forms with Azure Document intelligence
- Introduction
- What is Azure Document Intelligence?
- Get started with Azure Document Intelligence
- Train custom models
- Use Azure Document Intelligence models
- Use the Azure Document Intelligence Studio
- Exercise - Extract data from custom forms
- Module assessment
- Summary
- Create a knowledge mining solution with Azure AI Search
- Introduction
- What is Azure AI Search?
- Extract data with an indexer
- Enrich extracted data with AI skills
- Search an index
- Persist extracted information in a knowledge store
- Exercise - Create a knowledge mining solution
- Module assessment
- Summary
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