Skip to main content
Structure and Dynamics of Complex Networks
Graduate Program (& Advanced Certificate) Status
Course Description

The aim of this course is to get acquainted with some important topics at the frontier of network science. You need to have previous knowledge on complex networks to attend this course (see prerequisites).

Learning activities and teaching methods

The bulk of the course will be provided in lectures. Preparation for the classes involves the reading of selected papers, which will be discussed. The individual project consists of carrying out a small project, working through some papers and presenting results to the class.

Topics

  • Community detection
  • Clubs and cores
  • Random walks
  • Synchronization
  • Epidemic Spreading
  • Social dynamics
  • Evolutionary games
  • Temporal networks
  • Multilayer networks
  • Higher-order interactions
Learning Outcomes

By successfully absolving the course the students will be able to:

  • navigate a consistent part of the present day literature on the structure and dynamics of complex networks;
  • be able to identify specific research problems in network science and get access to tools needed to solve them.
Assessment

Students are expected to attend lectures during the course and to develop a project during the entire term. 

Grading: 

  • Attendance of the classes and homework: 30% of the final grade 
  • Final project: 70% of the final grade 
Prerequisites

Completing DNDS 6000 Fundamental Ideas in Network Science and DNDS 6013/6288 Scientific Python is required.

Course Level
Doctoral
Academic Year
2023-2024
Term
Winter
US Credits
2
ECTS Credits
4
Course Code
DNDS 6004