Dates
| weekly | Thursday | 14:15 - 15:45 | 06.04.2026 - 30.04.2026 | C 12.013 Seminarraum |
| weekly | Thursday | 14:15 - 15:45 | 21.05.2026 - 10.07.2026 | C 12.013 Seminarraum |
| single appointment | Th, 09.07.2026, 16:15 - Th, 09.07.2026, 17:45 | C 12.107 Seminarraum |
Curriculum context
Referat (50%)
Resit date: No resit date will be offered to this assessment, because it is didactically inseparably connected with one of the associated courses. A resit will only be possible, if the module is available again.
Organizational information
Registration
Registration ends 07.4.2026 at 23:59 h
Persons
Content
Students learn and apply basic concepts of Network Science.
Specialized Knowledge:
· graph theoretical foundations
· network metrics (graph level / node level / similarity)
· models of random graphs
- embedding of networks (shallow embeddings / deep embeddings)
· basic clustering methods
Professional Competences:
· analysis of networks with appropriate software tools (e.g. NetworkX, Neo4J)
· knowing how to handle relational data in data science projects
Personal competence:
Students, as teamwork, can develop project goals and time those realistically. Furthermore, they can reflect on their working results and evaluate them.
Evaluation
Further information on teaching evaluation: https://www.leuphana.de/en/teaching/quality-management/feedback-instruments.html