12 July 2024
Quantitative Methods in Complexity Research
The course will focus on an overview of various quantitative methods of complexity research. We will begin with the mathematical framework of stochastic processes and dynamical systems, commonly used to represent complex systems in mathematical terms. Then we will proceed to more directly applied subjects: Monte Carlo methods, used to simulate processes too complex to be mathematically tractable; graph theory and network analysis, used to describe and analyze systems decomposable into discrete interacting components; and machine learning. The latter will be discussed both as a tool for analysis of complex systems, in particular for classification and pattern detection, and as a tool for processing of data unsuitable for direct statistical analysis (such as natural language data). The focus of the course will be on which method to choose for a particular analysis task (what kind of questions the method is designed to answer, what kinds of data it requires, what are its assumptions, etc.) rather than how to apply it.
Course leader
Magdalena Kossowska-Lai, PhD, Jagiellonian University (Poland)
Target group
The course is intended for all students of all levels.
Fee info
EUR 650: The participant pays fees for:
a) participation in three selected courses with accommodation (7 days) and meals EUR 650
b) participation in three selected courses without accommodation with meals EUR 570
c) participation in three selected courses with accommodation (7 days) without meals EUR 620
d) participation in three courses without accommodation and meals EUR 450
e) each subsequent course EUR 150
f) optional trip EUR 50
Scholarships
No scholarships will be provided.