Network Science

Profile description and modules:

Description: 

Computational methods for the analysis of social and other complex networks.

Modules:

Network Analysis; Algorithms; Data Analysis

The profile focuses primarily on the following:

Learning objective is the acquisition of methodologically and theoretically founded skills for dealing with network data, in order to enable students to setup models, perform analyses, and create visualizations of network data primarily originating from empirical research.
The focus is on relevant mathematical and algorithmic problems; in addition, students will be introduced to existing software for analysis and visualization (visone, R, Siena, KNIME) that may also be developed further in master projects and theses.

Study structure:

Compulsory advanced courses

Advanced courses from the Computer Science Department:

  • Network Analysis (4+2 lectures/week, summer term)

  • Network Modeling (2+2 lectures/week, winter term

  • Network Dynamics (2+2 lectures/week, winter term)

Graduation area of studies:

  • MA-seminars and MA-projects in Algorithmics and Theoretical Computer Science

Elective advanced courses

Advanced courses from the Computer Science Department:

  • Design and Analysis of Algorithms (4+2 lectures/week, winter term)

  • Complexity Theory (4+2 lectures/week, summer term)

  • Principles of Data Mining (2+2 lectures/week, winter term)

  • Big Data and Scripting (4+2 lectures/week, summer term)

  • Graph Drawing (4+2 lectures/week, summer term)

  • Information Visualization I/II (2+2 lectures/week, winter/summer term)

For a detailed course description please use our course catalogue.

Research groups involved

Prof. Ulrik Brandes, AG Algorithmics

Prof. Sven Kosub, AG Algorithmics (Theory of Computing) 

Dr. Jürgen Lerner, AG Algorithmics

Area of application:

Focusing on methods, this study profile provides many links to application areas where network data are being collected. This includes, for instance,  sociology, public health, archaeology, logistics, infrastructure, telecommunications/Internet, media and marketing, biotechnology, finance, politics, and administration.

Contact and Mentor recommendation:

Prof. Ulrik Brandes, AG Algorithmics

Prof. Sven Kosub, AG Algorithmics (Theory of Computing)