Machine Learning for New Media Art – P06W17-20

Date: Jul 02 - 03, 2020

Skill Level(s): II to IV i

Instructor(s): Gene Kogan

Price Option(s):
$325 — Reduced Tuition (COVID-19 Artist Relief Offer)
$995 — Full Price Tuition (For those able to pay at this time)

Students may choose to pay the Reduced Tuition or the Full Price Tuition. Additional need-based scholarships available upon request.


Step into the future during this two-day workshop that surveys the application of machine learning to new media art. Participants engage in an overview of emerging techniques for processing multimedia data toward the creation of AI-assisted generative art and interactive installation. Current technical skills and practical resources for implementation are facilitated by distributing a collection of readymade software tools. Students produce novel artworks within the specific contexts inspiring to them. The course supplements practical training with more theoretical and critical information of the field at large.


Apply classification and regression to image, webcam, sound and text data, Procedural algorithms for generative art, Using cloud computation resources


Gene Kogan is an artist who is interested in generative systems, artificial intelligence and software for creativity and self-expression. He is a collaborator within numerous open-source software projects and leads workshops and demonstrations on topics at the intersection of code and art. Gene initiated ml4a, a free book about machine learning for artists, activists and citizen scientists.

Additional Information: Two-day virtual classes meet Thursday – Friday from 9-11AM and 1-4PM MST via Zoom Video Conferencing software (download free from An Anderson Ranch staff member co-teaches the class and coordinates the online platform. There can be a group critique Friday afternoon to wrap up the class. Further details will be emailed to registrants.

Image Courtesy of Gene Kogan

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