Network science

Profile description and modules

Description

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

Modules

Network analysis; algorithms; data analysis

Focus areas

The main learning objective is the acquisition of methodologically and theoretically founded skills for dealing with network data, enabling students to set up models, perform analyses, and create visualisations 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 visualisation (visone, R, Siena, KNIME) that may also be developed further in master's projects and theses.

Structure

Compulsory advanced courses

Compulsory courses offered by the Department of Computer and Information Science:

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

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

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

Towards the end of your degree:

  • Master's seminars and master's projects in algorithmics and theoretical computer science

Elective advanced courses

Elective courses offered by the Department of Computer and Information Science:

  • 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 detailed course descriptions, please see the course catalogue.

Research groups involved

Professor Ulrik Brandes, AG Algorithmics

Professor Sven Kosub, AG Algorithmics (Theory of Computing) 

Dr Jürgen Lerner, AG Algorithmics

Area of application

Focusing on methodologies, this area of specialisation provides many links to areas of application where network data is being collected. This includes, for instance, sociology, public health, archaeology, logistics, infrastructure, telecommunications/internet, media and marketing, biotechnology, finance, politics and administration.

Contact persons and mentor recommendations:

Professor Ulrik Brandes, AG Algorithmics

Professor Sven Kosub, AG Algorithmics (Theory of Computing)