CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and pr
ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica
EE-559: Deep learningThis course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.
CS-457: Geometric computingThis course will cover mathematical concepts and efficient numerical methods for geometric computing. We will explore the beauty of geometry and develop algorithms to simulate and optimize 2D and 3D g
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi
MGT-502: Data science and machine learningHands-on introduction to data science and machine learning. We explore recommender systems, generative AI, chatbots, graphs, as well as regression, classification, clustering, dimensionality reduction
