This course runs for a duration of 5 days.
The class will run daily from 9 AM ET to 5 PM ET.
Class Location: Virtual LIVE Instructor Led - Virtual Live Classroom.
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.
Audience profile
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.
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
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
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
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
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
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
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
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
9 - Get started with AI agent development on Azure
What are AI agents?
Options for agent development
Azure AI Foundry Agent Service
Module assessment
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
11 - Integrate custom tools into your agent
Why use custom tools
Options for implementing custom tools
How to integrate custom tools
Module assessment
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
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
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
15 - Integrate MCP Tools with Azure AI Agents
Understand MCP tool discovery
Integrate agent tools using an MCP server and client
Module assessment
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
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
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
19 - Create a custom text classification solution
Understand types of classification projects
Understand how to build text classification projects
Module assessment
20 - Custom named entity recognition
Understand custom named entity recognition
Label your data
Train and evaluate your model
Module assessment
21 - Translate text with Azure AI Translator service
Provision an Azure AI Translator resource
Specify translation options
Define custom translations
Module assessment
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
23 - Translate speech with the Azure AI Speech service
Provision an Azure resource for speech translation
Translate speech to text
Synthesize translations
Module assessment
24 - Develop an audio-enabled generative AI application
Deploy a multimodal model
Develop an audio-based chat app
Module assessment
25 - Analyze images
Provision an Azure AI Vision resource
Analyze an image
Module assessment
26 - Read text in images
Explore Azure AI options for reading text
Read text with Azure AI Vision Image Analysis
Module assessment
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
28 - Classify images
Azure AI Custom Vision
Train an image classification model
Create an image classification client application
Module assessment
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
30 - Analyze video
Understand Azure Video Indexer capabilities
Extract custom insights
Use Video Analyzer widgets and APIs
Module assessment
31 - Develop a vision-enabled generative AI application
Deploy a multimodal model
Develop a vision-based chat app
Module assessment
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
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
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
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
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
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
Before attending this course, students must have:
