AI & ML Academy
Welcome to the AI and ML Academy (AIA)! This academy includes 6 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:
Our ongoing vignettes continue the series by looking at the latest AI & ML topics:
- Microsoft Build (developer conference) - May 23-24. Join live or watch recordings on-demand! See Microsoft Build 2023 Recommended AI Session Guide
- Microsoft Build Recap: Insights and Learnings for Analytics and AI - June 7 - Registration page
- AI Readiness events: AI & ML Partner Prep
Table of Contents
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||General-purpose AI Cognitive Services, including Vision, Speech, Language
Customization of these Cognitive Services
|Azure OpenAI||Generative AI, including GPT, Codex, DALL-E, and Chat GPT|
|Applied AI||Form Recognizer, Metrics Advisor, Cognitive Search, Video Analyzer, Bot service, Immersive Reader etc.|
|Build Your Own ML||Custom ML with Notebooks, Auto ML, Designer using Azure ML|
|ML Platform||Train and Deploy models across a host of environments and compute types|
|ML Engineering in Production (MLOps)||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:
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. Curious how to contribute? See our Contribution Cheat Sheet.