Fundamental Ideas in Network Science

Course Level: 
Master’s
Doctoral
Campus: 
Vienna
Course Open to: 
Students on-site
Remote students
Academic Year: 
2020-2021
Term: 
Fall
US Credits: 
4
ECTS Credits: 
8
Course Code: 
DNDS 6000
Course Description: 

This is an interdisciplinary course and students with different backgrounds are expected to register for it. The aim is to get acquainted with the basic concepts of network science, including elements of the theory of graphs, dynamics of and on networks, as well as with basic applications from biology, sociology, economics and other fields.

Learning activities and teaching methods

Class sessions include lectures and training to the network visualization software Gephi. There are regular home assignments to deepen the understanding of the basic concepts and methods. Students write a Wikipedia-style essay about a self-chosen topic related to network science. They carry out project work for which they have to collect the data, analyze it and finally present the results in class, where they are discussed. The project is prepared in pairs or individually. The course has an e-learning site with learning material, where instructions, discussions can be performed. 

Learning Outcomes: 

By successfully completing the course, students will be able to:

  • Recognize the importance of the network approach in their own fields of studies;
  • Map out networks from data on complex systems in diverse fields of applications and use simple visualization softwares;
  • Carry out statistical analysis of complex networks regarding the basic characteristics;
  • Measure dynamic properties of processes on networks;
  • Attend the more specialized courses.
Assessment: 
For grade, students are expected to:
  • solve the homework tasks (10%)
  • complete two assignments (one at home (10%) and the other one, the midterm, in class (20%)),
  • submit the essay (20%) and
  • present the results of the project work (40%). 
For audit, students are expected to:
  • solve the homework tasks,
  • complete the first assignment (completed at home) and
  • submit the essay.
Prerequisites: 

Mostly elementary math prerequisites are assumed, the tools needed will constitute part of the course.