Fall 2024

Instructor: Grigore Burloiu

📜 Course Description

This semester introduces Machine Learning as a practical tool for interactive system design. The first half of the course focuses on interactive machine learning for interface design: defining input and output spaces by example and learning from data. The second half introduces deep learning techniques for artistic material generation and manipulation. At the end, students are equipped with knowledge and techniques needed for advanced interaction design and exploration.

🗝 Course Prerequisites

This class builds on the creative coding foundation acquired in the first year. Previous experience with machine learning is a plus, but not required.

🧠 Course Objectives

Students in this course will:

obtain an intuition of machine learning models and techniques for advanced interaction and control
use stochastic processes to generate material
create complex real-time interaction schemas for mixed-media art projects
master domain-specific programming tools
gain applied knowledge of machine learning theory and techniques
understand key issues of ML and data ethics