Designing and Implementing an Azure AI Solution

Generative Artificial Intelligence (AI) is becoming more accessible through comprehensive development platforms like Azure AI Foundry. Learn how to build generative AI applications that use language models to chat with your users.

Lessons:

• Plan and prepare to develop AI solutions on Azure
• Choose and deploy models from the model catalog in Azure AI Foundry portal
• Develop an AI app with the Azure AI Foundry SDK
• Get started with prompt flow to develop language model apps in the Azure AI Foundry
• Develop a RAG-based solution with your own data using Azure AI Foundry
• Fine-tune a language model with Azure AI Foundry
• Implement a responsible generative AI solution in Azure AI Foundry
• Evaluate generative AI performance in Azure AI Foundry portal

Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This learning path will help you understand the AI agents, including when to use them and how to build them, using Azure AI Foundry Agent Service and Semantic Kernel Agent Framework. By the end of this learning path, you will have the skills needed to develop AI agents on Azure.

Lessons:

• Get started with AI agent development on Azure
• Develop an AI agent with Azure AI Foundry Agent Service
• Integrate custom tools into your agent
• Develop an AI agent with Semantic Kernel
• Orchestrate a multi-agent solution using Semantic Kernel

Natural language solutions use language models to interpret the semantic meaning of written or spoken language, and in some cases respond based on that meaning. You can use the Language service to build language models for your applications, and explore Azure AI Foundry to use generative models for speech.

Lessons:

• Analyze text with Azure AI Language
• Create question answering solutions with Azure AI Language
• Build a conversational language understanding model
• Create a custom text classification solution
• Custom named entity recognition
• Translate text with Azure AI Translator service
• Create speech-enabled apps with Azure AI services
• Translate speech with the Azure AI Speech service
• Develop an audio-enabled generative AI application

Computer vision is an area of artificial intelligence that deals with visual perception. Azure AI includes multiple services that support common computer vision scenarios.

Lessons:

• Analyze images
• Read text in images
• Detect, analyze, and recognize faces
• Classify images
• Detect objects in images
• Analyze video
• Develop a vision-enabled generative AI application
• Generate images with AI

Use Azure AI to extract information from content to support scenarios like:Data captureBusiness process automationMeeting summarization and analysisDigital asset management (DAM)Knowledge Mining

Lessons:

• Create a multimodal analysis solution with Azure AI Content Understanding
• Create an Azure AI Content Understanding client application
• Use prebuilt Document intelligence models
• Extract data from forms with Azure Document intelligence
• Create a knowledge mining solution with Azure AI Search