AI-102 : Develop AI solutions in Azure

Plan and prepare for the development of AI solutions on Azure

• Identify common AI features that you can implement in apps
• Describe Azure AI services and considerations for using them.
• Describe Azure AI Foundry and considerations for using it.
• Identify the appropriate development tools and SDKs for an AI project
• Describe responsible AI considerations

Develop an AI application with the Azure AI Foundry SDK

• Describe the features of the Azure AI Foundry SDK.
• Use the Azure AI Foundry SDK to work with connections in projects
• Use the Azure AI Foundry SDK to develop an AI chat app

Get started with the prompt flow to develop language model apps in Azure AI Studio

• Be aware of the development lifecycle when building language model applications
• Understand what a flow looks like in a prompt flow
• Explore the main components when using the prompt flow

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

• Identify the need to anchor your language model with Augmented Generation Recovery (RAG)
• Index your data using Azure AI Search so that it can be searched for language models
• Create an agent using RAG on your own data in the Azure AI Foundry portal

Tune a language model with Azure AI Foundry

• Understand when to optimize a model.
• Prepare your data to optimize a conversation completion model.
• Adjust a base model in the Azure AI Foundry portal.

Implement a responsible generative AI solution in Azure AI Foundry

• Describe a global process for the development of responsible ARTIFICIAL INTELLIGENCE solutions
• Identify and prioritize potential damage relevant to a generative AI solution
• Measuring the presence of damage in a generative AI solution
• Mitigating the Damage in a Generative AI Solution
• Prepare for the deployment and operation of a generative AI solution responsibly

Evaluate generative AI performance in the Azure AI Foundry portal

• Understand the reference points of the models.
• Perform manual evaluations.
• Evaluate your generative AI applications with AI-assisted metrics.
• Configure assessment workflows in the Azure AI Foundry service.

Get started with AI agent development on Azure

• Describe the fundamental concepts related to AI agents
• Describe agent development options
• Create and test an agent in the Azure AI Foundry portal

Develop an AI agent with Azure AI Foundry Agent Service

• Describe the purpose of AI agents
• Explain the key features of the Azure AI Foundry Agent service.
• Create an agent using the Foundry Agent Service
• Integrate a Foundry Agent Service Agent with Your Own Application

Integrate custom tools with your agent

• Describe the benefits of using custom tools with your agent.
• Explore the different options for custom tools
• Create an agent that integrates with custom tools using the Azure AI Foundry Agent service

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

• Describe how connected agents enable modular, collaborative workflows.
• Design a multi-agent solution by defining the main agent tools and connected agent roles
• Build and run a connected agent solution

Integrate MCP Tools with Azure AI Agents

• Explain the roles of the MCP server and client in discovering and calling tools.
• Encapsulate MCP tools as asynchronous functions and register them with Azure AI agents
• Create an Azure AI agent that dynamically accesses and invokes MCP tools during runtime

Develop an AI agent with the semantic core

• Use the semantic kernel to connect to an Azure AI Foundry project
• Create Azure AI Foundry service agents using the Semantic Core SDK
• Integrate plug-in features with your AI agent

Orchestrate a multi-agent solution using the semantic kernel

• Build AI agents using the Semantic Kernel SDK
• Develop multi-agent solutions
• Create custom selection and termination policies for agent collaboration

Analyze text with Azure AI Language

• Detect the language of the text
• Analyze the sentiment of the text
• Extract key phrases, entities, and related entities

Build question-answering solutions with Azure AI Language

• Understanding the answer to questions and how it compares to language comprehension
• Create, test, publish, and use a knowledge base
• Implement multi-turn conversation and active learning
• Create a question-answering bot to interact with natural language usage

Create a Everyday Language Understanding Model

• Provision Azure resources for the Azure AI Language resource
• Define intentions, statements, and entities
• Use templates to differentiate between similar statements
• Use predefined entity components
• Train, test, publish, and review an Azure AI Language model

Create a custom text classification solution

• Understanding the Types of Classification Projects
• Create a custom text classification project
• Tag data, train and deploy a model
• Send classification jobs from your own application

Recognize custom named entities

• Understanding Markup Features in Drillthrough Projects
• Understand how to create entity recognition projects

Translate text with the Azure AI Translator service

• Provision a Translator resource
• Understanding Language Detection, Translation, and Transliteration
• Specify translation options
• Define custom translations

Build apps with speech recognition using Azure AI services

• Provision an Azure resource for the Azure AI Speech service
• Implement speech recognition with Azure AI’s Speech-to-Text API
• Use the text-to-speech API to implement text-to-speech
• Set up audio format and voices
• Use Speech Synthesis Markup Language (SSML)

Perform speech translation with the Azure AI Speech service

• Provision Azure resources for speech translation
• Generate a text translation from speech recognition
• Synthesize spoken translations

Develop an audio-enabled generative AI application

• Deploy an audio-enabled generative AI model in Azure AI Foundry
• Create a chat app that sends audio prompts

Analyze images

• Provision an Azure AI Vision resource.
• Use the Azure AI Vision SDK to connect to your resource.
• Write code to analyze an image.

Read text in images

• Describe the OCR capabilities of the Azure AI Vision Image Analysis API.
• Use the Azure AI Vision Service Image Analysis API to extract text from images.

Detect, analyze and recognize faces

• Describe the capabilities of Azure AI Vision’s Face service.
• Write code to detect and analyze faces in an image
• Describe facial recognition support in Azure AI Vision Face
• Describe responsible AI considerations when developing facial solutions

Classify images

• Provision Azure resources for Azure AI Custom Vision
• Train an image classification model
• Use the Azure AI Custom Vision SDK to build an image classification client application

Detect objects in images

• Provision Azure resources for Azure AI Custom Vision
• Understanding Object Detection
• Train an object detector
• Use the Azure AI Custom Vision SDK to build an object detection client application

Analyze a video

• Describe the capabilities of Azure Video Indexer
• Extract custom insights
• Use Azure Video Indexer APIs and widgets

Develop a Vision-Enabled Generative AI Application

• Deploy a vision-enabled generative AI model in Azure AI Foundry.
• Test an image-based prompt in the conversation playground.
• Create a chat app that sends image-based prompts.

Generate images using AI

• Describe the features of image generation models
• Use the image playground in the Azure AI Foundry portal
• Integrate image generation models into your applications

Build a modal analytics solution with Azure AI Content Understanding

• Describe Azure AI content understanding capabilities
• Use Azure AI content understanding to create a content analyzer
• Use a content comprehension analyzer using the REST API

Create an Azure AI Content Understanding client application

• Use the Azure AI Content Understanding REST API to generate a content analyzer
• Use the Azure AI Content Understanding REST API to consume an analyzer

Use predefined Document Intelligence templates

• Identify business problems that you can solve using predefined templates in Forms Analyzer
• Analyze forms using the general, read, and layout document templates
• Analyze forms using predefined financial, ID, and tax templates

Extract data from forms with Azure Document Intelligence

• Identify how Document Intelligence’s layout service, predefined templates, and custom templates can automate processes
• Use Document Intelligence features with SDKs, REST API, and Document Intelligence Studio
• Develop and test custom models

Build a knowledge mining solution with Azure AI Search

• Implement indexing with Azure AI Search
• Use AI capabilities to enrich data in an index
• Search an index to find relevant information
• Maintain extracted information in a knowledge base

Updated on 08/05/2025.

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