101-0139-00L Scientific Machine and Deep Learning for Design and Construction (HS24)

This course aims to provide a graduate-level introduction to machine learning, with a particular focus on scientific machine learning for applications in the design and construction phases of projects from architecture and civil engineering. In a series of comprehensive exercises and in-lab demonstrations the students will learn to:

1. Understand main machine learning background theory and methods.
2. Assess a problem and apply machine and deep learning techniques in a computational framework accordingly.
3. Incorporate scientific domain knowledge in the scientific computing workflow.
4. Define, plan, conduct and present a scientific model developed for a target application.

Organization

Prof. Bernd Bickel

Dr. Andreas Müller

Dr. Michal Piovarci

Rafael Bischof

Chair of Computational Design, ETH Zurich

Location

Course material is available at ETHZ Moodle

Physical lectures take place at HCI E8 (ETH Hoenggerberg)