- COURSE
Designing and Implementing a Microsoft Azure AI Solutions (AI-102T00)
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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. The course will use C# or Python as the programming language.
Upcoming Class Dates and Times
All Sunset Learning courses are guaranteed to run
Course Outline and Details
Prerequisites
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
Target 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.
Course Objectives
- 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 date 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
Course Outline
Plan and prepare to develop AI Solutions on Azure
- What is AI?
- Azure AI services
- Azure AI Foundry
- Developer tools and SDKs
- Responsible AI
- Exercise-Prepare for an AI development project
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
- Exercise-Explore, deploy and chat with language models
Develop an AI app with the Azure AI Foundry SDK
- What is the Azure Ai Foundry SFK?
- Work with project connections
- Create a chat client
- Exercise-Create a Generative AI chat app
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
- Exercise-Get started with prompt flow
Develop a RAG-based solution with your own date 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
- Exercise-Create a Generative AI app that uses your own data
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 Studio
- Exercise-Fine-tune a language model
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
- Exercise-Apply content filters to prevent the output of harmful content
Evaluate Generative AI performance in Azure AI Foundry portal
- Assess the model performance
- Manually evaluate the performance of a model
- Automated evaluations
- Exercise-Evaluate Generative Ai model performance