Special topics in Condensed Matter II: Artificial Intelligence and Complex Dynamical Systems (Φ-842)

Γιώργος Τσιρώνης


Goal of the course


 The course introduces methods of Artificial Intelligence (AI) and in particular Machine Learning (ML) in Complex Dynamical Systems.  The aim is two-fold; on one hand it presents a very basic introduction to ML while, on the other hand, it uses the ML methods  in the study of Complex systems.  Prerequisites include basic computational tools and knowledge of classical and quantum mechanics.  Expected outcomes: Knowledge of ML and Complex Systems and practical use of various ML techniques.

If there will be students that cannot follow the course in class we will have a (partial) on-line mode.  The on-line lectures will be given through:  https://hou.webex.com/meet/tsironis.georgios. This aspect will be discussed during the first week of classes.



Brief introduction to Machine Learning, types of ML, standard methods of regression, support vector machines, trees and forests, artificial neural networks.

Introduction to basic concepts of nonlinear dynamical syst