Introduction to Azure AI, AI Studio and LLMOps
Course Description
In this two-day course, participants will start the morning with an introduction to the capabilities of Artificial Intelligence and Machine Learning available in Azure. The focus of this course will be about enabling citizen developers to use readily available, easily accessible tools, to improve quality, accuracy, and speed. Students will learn how to use AI Builder to process various types of documents in a workflow.
In the afternoon, the focus will switch to an introduction into one of the newest features available Copilot Studio and from there will go into the more advanced Azure AI Studio. It offers more enterprise features that allow you to collaborate on AI projects as a team and build out more complex bots and easily create a bot that searches your own data.
On day two the focus will switch to an overview of providing a structured approach to developing LLM-infused applications, guiding users through building, testing, optimizing, and deploying flows. This streamlined process results in the creation of fully functional LLM-infused solutions.
Throughout the course students will complete challenge-based tasks in Azure to understand the concepts in a hands-on manner.
About this Course
Course Outline
Modules Day 1
- Overview
- AI/ML Introduction
- AI Builder overview
- Extract information from invoices
- Extract text in photos and PDF documents
- Extract custom information from documents
- Copilot Studio overview
- Azure AI Studio overview
- Explore AI Studio
- Get started with prompt flow
- Create a custom copilot that uses your own data
Modules Day 2
- Introduction to Azure Machine Learning and Prompt Flow
- Overview of Azure Machine Learning capabilities
- Introduction to Prompt Flow in Azure Machine Learning
- Understanding the LLMOps with Prompt Flow
- Setting Up Your Environment
- Configuring Azure DevOps for machine learning projects
- Establishing a code repository for Prompt Flow
- Preparing your local environment for Prompt Flow development
- Developing with Prompt Flow
- Exploring the Prompt Flow features and lifecycle
- Managing code with centralized hosting
- Implementing variant and hyperparameter experimentation
- Deployment and Testing
- Understanding deployment targets and Docker integration
- Executing A/B deployments and evaluating results
- Managing datasets and model registration
- CI/CD Integration
- Integrating Prompt Flow with CI/CD pipelines
- Versioning and managing releases with Azure DevOps
- Transitioning from local to cloud environments
Duration
2 Days
Prerequisites
none
Level
Beginner
Product
- Azure AI
- AI Studio
Role
- Citizen developers
- Business users
- Business Analysts and Strategists
- Cloud Technology Enthusiasts