Creative Coding
A hands-on, code-first journey through modern music AI — from audio features and VAEs to transformers and diffusion models — building working generative systems in Python. Includes guest sessions with Jordan Rudess and Christian Steinmetz.
An Introduction to AI Music (50')
Over 12 sessions this course takes developers from the fundamentals of machine learning for audio through to the architectures powering today's generative music tools. You'll set up a Python environment, work with MIDI and spectrogram representations, and get hands-on with RAVE, EnCodec, Anticipatory Music Transformers, MusicGen and Stable Audio. Later sessions cover real-time inference (TorchScript, quantization, ONNX) and the commercial landscape, before you scope, build and present your own final project. Designed for developers comfortable with Python who want to understand and build music-AI systems rather than just use them.
2 videos, 1 resource, 2 lessons
6 videos, 3 lessons
6 videos, 2 lessons
2 videos, 2 lessons
4 videos, 2 lessons
5 videos, 2 lessons
3 videos, 2 lessons
8 videos, 2 lessons
4 videos, 2 lessons
6 videos, 2 lessons
1 video, 2 lessons
1 video, 2 lessons
Lancelot Blanchard is a musician, engineer, and AI researcher at the MIT Media Lab's Responsive Environments group. His research focuses on generative AI systems for human-AI co-created live musical performances, pioneering the concept of Symbiotic Virtuosity in AI-human music collaboration. He has collaborated with Grammy-winning keyboardist Jordan Rudess and brings eight years of software engineering experience to his teaching.
One-off enrolment. Includes all course materials.