Tag Archives: python

class, elective, grad, grad-s25-studio, s25, special topic

DM-GY 9103 Conservation of AI-Based Artworks

The newest artist is AI. As the landscape for creating and displaying AI-based artworks is fast-paced and ever-evolving, what are the common tools and languages that will be necessary to conserve and re-exhibit these works into the future? In this class, students will work on case studies in collaboration with a contemporary artist and their studio, focusing on artworks created using AI.  Students will learn conceptual and practical frameworks of conservation as applied in this field through readings, class discussion and guest lectures, along with lab sessions to learn and apply skills to handle these artworks. Throughout the semester students will develop documentation and present conservation concepts for these fragile artworks.

Previous programming experience is highly recommended. Please contact instructors for  evaluation and guidance related to your current programming expertise related to this class.

Instructors: Thiago Hersan, Deena Engel

elective, grad, grad-s25-studio, s25, special topic

DM-GY 9103 Deep Learning For Media

Deep learning has promoted breakthroughs in managing and creating media content, and continues to shape the future of the multimedia landscape. This course provides a hands-on, project-oriented introduction to deep learning for the classification, retrieval, and creation of media content, with emphasis in audio-visual content. Students create and work with existing deep learning models and Python libraries, and think critically about the application of these models for media.

Instructor : Magdalena Fuentes

Sample Syllabus

class, elective, f24, grad, special topic

DM-GY 9103 Introduction to Machine Learning for Media

This course will introduce students to the wild and wonderful world of data analysis and machine learning from critical, practical and creative perspectives. Through readings, projects and programming assignments, students will develop a solid understanding of Machine Learning applications and techniques related to media processing, analysis and creation. We will use Python and Jupyter notebooks to run, fine tune and analyze existing machine learning models for creative media applications. Students should have prior programming experience.

Instructor: Thiago Hersan