Large Networks & Random Graphs - Interactive curriculae of TU Ilmenau
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| module properties Large Networks & Random Graphs in degree program Master Informatik 2021 | |
|---|---|
| module number | 200439 |
| examination number | 2400791 |
| department | Department of Mathematics and Natural Sciences |
| ID of group | 2417 (Combinatorics / Graph Theory) |
| module leader | Prof. Dr. Yury Person |
| term | summer term only |
| language | English |
| credit points | 5 |
| on-campus program (h) | 34 |
| self-study (h) | 116 |
| obligation | elective module |
| exam | oral examination performance, 30 minutes |
| details of the certificate | |
| link to Moodle course | |
| teacher | Person, Yury |
| signup details for alternative examinations | |
| maximum number of participants | |
| previous knowledge and experience | Stochastics (e.g. Diskrete Stochastik (200401) or Stochastik (200375), |
| learning outcome | Students are familiar with various models of random graphs, their potential applications as well as advantages and disadvantages. They can select a suitable model for an application problem, examine it methodologically and apply and develop algorithms for it. They are also able to read current literature in the context of scientific research at the time. They can present the results and conclusions and are able to discuss and reflect them. |
| content | Models of random graphs G(n,p), G(n,m), G(n,d) and their most important properties. Thresholds and expectation thresholds. Random geometric graphs and models for complex networks. Algorithms on random graphs. |
| media of instruction and technical requirements for education and examination in case of online participation | Moodle, slides or PC presentations, blackboard and worksheets |
| literature / references | B. Bollobás: Random Graphs, 2nd edition; Cambridge University Press, 2001. |
| evaluation of teaching | |