AI & ML Academy

Content

Welcome to the AI and ML Academy (AIA)! This academy includes 5 modules, all of which build on top of each other. It incorporates technical assets as well as best practices. We include common AI/ML scenarios that we have seen throughout various industries. The objective of the academy is to help you all move faster and build effective solutions. The modules are:

Prebuilt AI

Applied AI

Build Your Own ML

Azure Machine Learning Platform

ML Engineering in Production (MLOps)

Vignettes

Our ongoing vignettes continue the series by looking at the latest AI & ML topics:

Azure OpenAI Business Briefing February 27, 2023

Azure OpenAI Technical Briefing February 28, 2023

Azure OpenAI in Financial Services March 14, 2023

Live Schedule

We’ll update this section with our upcoming Partner prep series and AI shows available as a webcast and all content will be included here.

The structure of the content is represented in the table below; the overview session is a high level overview focusing on concepts and principles, while each of the ‘module’ sessions, Pre-Built AI through MLOps, will be more in-depth. Each session will contain one or more presentations, with several suggested labs and workshop content in each module designed to accomodate various skill levels and time availability.

Refer to links below for the module breakouts.

AI & ML Overview
Prebuilt AI	Applied AI	Build Your Own ML	ML Platform	ML Engineering in Production (MLOps)
General-purpose AI Cognitive Services, including Vision, Speech, Language Customization of these Cognitive Services	Form Recognizer, Metrics Advisor, Cognitive Search, Video Analyzer, Bot service, Immersive Reader etc.	Custom ML with Notebooks, Auto ML, Designer using Azure ML	Train and Deploy models across a host of environments and compute types	Azure DevOps GitHub Actions KubeFlow

Hands-on provisioned Environments

We are not currently offering fully-hosted lab environments for AI & ML Academy, but this may change in the future as we expand the content. In the meantime, you can still run the labs in your own Azure subscription. These labs are listed below:

Contributions

We welcome contributors to this project. Please use the GitHub links near the upper right and consider submitting pull requests or filing issues as needed.