(Online Delivery) AI-102T00 Develop AI solutions in Azure

Before attending this course, students must have:

• Knowledge of Microsoft Azure and ability to navigate the Azure portal
• Knowledge of either C# or Python
• Familiarity with JSON and REST programming semantics

Agenda

Lesson 1 - Plan and prepare to develop AI solutions on Azure

• What is AI?
• Azure AI services
• Azure AI Foundry
• Developer tools and SDKs
• Responsible AI
• Module assessment

Lesson 2 - Choose and deploy models from the model catalog in Azure AI Foundry portal

• Explore the model catalog
• Deploy a model to an endpoint
• Optimize model performance
• Module assessment

Lesson 3 - Develop an AI app with the Azure AI Foundry SDK

• What is the Azure AI Foundry SDK?
• Work with project connections
• Create a chat client
• Module assessment

Lesson 4 - Get started with prompt flow to develop language model apps in the Azure AI 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
• Module assessment

Lesson 5 - Develop a RAG-based solution with your own data using Azure AI Foundry

• Understand how to ground your language model
• Make your data searchable
• Create a RAG-based client application
• Implement RAG in a prompt flow
• Module assessment

Lesson 6 - Fine-tune a language model with Azure AI 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 Azure AI Foundry portal
• Module assessment

Lesson 7 - Implement a responsible generative AI solution in Azure AI Foundry

• Plan a responsible generative AI solution
• Map potential harms
• Measure potential harms
• Mitigate potential harms
• Manage a responsible generative AI solution
• Module assessment

Lesson 8 - Evaluate generative AI performance in Azure AI Foundry portal

• Assess the model performance
• Manually evaluate the performance of a model
• Automated evaluations
• Module assessment

Lesson 9 - Get started with AI agent development on Azure

• What are AI agents?
• Options for agent development
• Azure AI Foundry Agent Service
• Module assessment

Lesson 10 - Develop an AI agent with Azure AI Foundry Agent Service

• What is an AI agent
• How to use Azure AI Foundry Agent Service
• Develop agents with the Azure AI Foundry Agent Service
• Module assessment

Lesson 11 - Integrate custom tools into your agent

• Why use custom tools
• Options for implementing custom tools
• How to integrate custom tools
• Module assessment

Lesson 12 - Develop an AI agent with Semantic Kernel

• Understand Semantic Kernel AI agents
• Create an Azure AI agent with Semantic Kernel
• Add plugins to Azure AI agent

Lesson 13 - Orchestrate a multi-agent solution using Semantic Kernel

• Understand the Semantic Kernel Agent Framework
• Create an agent group chat
• Design an agent selection strategy
• Define a chat termination strategy

Lesson 14 - Develop a multi-agent solution with Azure AI Foundry Agent Service

• Understand connected agents
• Design a multi-agent solution with connected agents
• Module assessment

Lesson 15 - Integrate MCP Tools with Azure AI Agents

• Understand MCP tool discovery
• Integrate agent tools using an MCP server and client
• Module assessment

Lesson 16 - Analyze text with Azure AI Language

• Provision an Azure AI Language resource
• Detect language
• Extract key phrases
• Analyze sentiment
• Extract entities
• Extract linked entities
• Module assessment

Lesson 17 - Create question answering solutions with Azure AI Language

• Understand question answering
• Compare question answering to Azure AI Language understanding
• Create a knowledge base
• Implement multi-turn conversation
• Test and publish a knowledge base
• Use a knowledge base
• Improve question answering performance
• Module assessment

Lesson 18 - Build a conversational language understanding model

• 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
• Module assessment

Lesson 19 - Create a custom text classification solution

• Understand types of classification projects
• Understand how to build text classification projects
• Module assessment

Lesson 20 - Custom named entity recognition

• Understand custom named entity recognition
• Label your data
• Train and evaluate your model
• Module assessment

Lesson 21 - Translate text with Azure AI Translator service

• Provision an Azure AI Translator resource
• Specify translation options
• Define custom translations
• Module assessment

Lesson 22 - Create speech-enabled apps with Azure AI services

• 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
• Module assessment

Lesson 23 - Translate speech with the Azure AI Speech service

• Provision an Azure resource for speech translation
• Translate speech to text
• Synthesize translations
• Module assessment

Lesson 24 - Develop an audio-enabled generative AI application

• Deploy a multimodal model
• Develop an audio-based chat app
• Module assessment

Lesson 25 - Analyze images

• Provision an Azure AI Vision resource
• Analyze an image
• Module assessment

Lesson 26 - Read text in images

• Explore Azure AI options for reading text
• Read text with Azure AI Vision Image Analysis
• Module assessment

Lesson 27 - 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
• Module assessment

Lesson 28 - Classify images

• Azure AI Custom Vision
• Train an image classification model
• Create an image classification client application
• Module assessment

Lesson 29 - Detect objects in images

• Use Azure AI Custom Vision for object detection
• Train an object detector
• Develop an object detection client application
• Module assessment

Lesson 30 - Analyze video

• Understand Azure Video Indexer capabilities
• Extract custom insights
• Use Video Analyzer widgets and APIs
• Module assessment

Lesson 31 - Develop a vision-enabled generative AI application

• Deploy a multimodal model
• Develop a vision-based chat app
• Module assessment

Lesson 32 - Generate images with AI

• What are image-generation models?
• Explore image-generation models in Azure AI Foundry portal
• Create a client application that uses an image generation model
• Module assessment

Lesson 33 - Create a multimodal analysis solution with Azure AI Content Understanding

• What is Azure AI Content Understanding?
• Create a Content Understanding analyzer
• Use the Content Understanding REST API
• Module assessment

Lesson 34 - Create an Azure AI Content Understanding client application

• Prepare to use the AI Content Understanding REST API
• Create a Content Understanding analyzer
• Analyze content
• Module assessment

Lesson 35 - Use prebuilt Document intelligence models

• Understand prebuilt models
• Use the General Document, Read, and Layout models
• Use financial, ID, and tax models
• Module assessment

Lesson 36 - Extract data from forms with Azure Document intelligence

• 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
• Module assessment

Lesson 37 - Create a knowledge mining solution with Azure AI Search

• 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
• Module assessment