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 Sabine Storandt, AG Algorithmics
Professor Sven Kosub, AG Algorithmics (Theory of Computing)