The Applied Machine Learning Intensive (AMLI) is a collection of content that can be used to teach machine learning. The original content was created for a 10-week, bootcamp-style course for undergraduate college students. Designed for students who weren’t necessarily majoring in computer science, the goal was to enable participants to apply machine learning to different fields using high-level tools.

The content primarily consists of slides, Jupyter notebooks, and facilitator guides. The slide decks are written in marp markdown syntax, which can be exported to other formats. The Jupyter notebooks were written in and targeted to run in Colab. The instructor guide as an odt document.

Applied Machine Learning Intensive instructional materials are available open source for faculty looking to run this program for students. This repository offers all slide decks, facilitation guides, labs, and gradable items. Because the program is considered academic in nature, we ask that interested faculty fill out the form below to receive a password to unlock the answer keys. We will provide you with a password that can be used to unlock the keys using a standard zip program or the tools/unlock_labs.py tool found in this repository.

Please fill out the following brief form to receive the answer keys for the curriculum:

https://docs.google.com/forms/d/e/1FAIpQLSd9v0az2wmKP659Xx5SlS7WPbQPD3u3yLXZMn0LHf3Vjj-ziw/viewform

The information that you submit will be maintained in accordance with Google’s Privacy Policy.

All course content (Colabs, slides, guides, and materials) are open sourced under the CC-BY-4.0 International license. All code contained in this course is open sourced under the Apache 2.0 license.

Attribution and license information for content not created by Google will be presented in the speaker notes.