MSc course in complexity science – Spring/Summer term 2024
This year I will open the course to external students. Lectures will be streamed, course material will be provided.
The course consists of lectures, discussion sessions, Jupyter notebook sessions, and mini projects. The course is targeted toward physics and mathematics (with basic physics knowledge) MSc and PhD students. Ideally, external students will spend a few days in Potsdam toward the end of the course.
8 April – 15 July , Mondays 8.15 am - 11.45 am CET
University of Potsdam, Golm Campus (train station Golm)
Physics Building, Nr 28 ("the golden cage")
Room 1.084 (1st floor)
U Potsdam students: please, sign up via PULS.
External students, please, sign up as "Nebenhörer" (info here) and also send me an email.
Course content:
Philosophical foundations of complexity / complexity science
Complex networks (mathematical basics, clustering, community detection, application to social networks)
Information theory (Shannon entropy and derived quantities, estimation techniques, application to time series analysis)
Black swans (rank-ordering and extreme value statistics, percolation and criticality, applications in climate science)
Selected topics
Literature:
What is a complex system, Yale University Press (2020)
Critical phenomena in natural sciences: chaos, fractals, selforganization and disorder: concepts and tools, Springer (2006)
MacKay, David JC. Information theory, inference and learning algorithms. Cambridge university press (2003)
Newman, Mark. Networks. Oxford university press, 2018.
Selected research papers
The course consists of lectures, discussion sessions, Jupyter notebook sessions, and mini projects. The course is targeted toward physics and mathematics (with basic physics knowledge) MSc and PhD students. Ideally, external students will spend a few days in Potsdam toward the end of the course.
8 April – 15 July , Mondays 8.15 am - 11.45 am CET
University of Potsdam, Golm Campus (train station Golm)
Physics Building, Nr 28 ("the golden cage")
Room 1.084 (1st floor)
U Potsdam students: please, sign up via PULS.
External students, please, sign up as "Nebenhörer" (info here) and also send me an email.
Course content:
Philosophical foundations of complexity / complexity science
Complex networks (mathematical basics, clustering, community detection, application to social networks)
Information theory (Shannon entropy and derived quantities, estimation techniques, application to time series analysis)
Black swans (rank-ordering and extreme value statistics, percolation and criticality, applications in climate science)
Selected topics
Literature:
What is a complex system, Yale University Press (2020)
Critical phenomena in natural sciences: chaos, fractals, selforganization and disorder: concepts and tools, Springer (2006)
MacKay, David JC. Information theory, inference and learning algorithms. Cambridge university press (2003)
Newman, Mark. Networks. Oxford university press, 2018.
Selected research papers
