250105 SE Complex Network Analysis Project (2022S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 07.02.2022 00:00 to Mo 21.02.2022 23:59
- Deregistration possible until Th 31.03.2022 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Details are announced on moodle. There will be four meetings of all course participants: One preparatory meeting at the beginning of the semester and three presentation meetings as detailed below. The exact dates will be announced shortly.
Thursday
17.03.
08:00 - 11:00
Seminarraum 12 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
Aims: The course follows up on the lecture “Introduction to complex network analysis” held in the previous semester. The students will develop and conduct a project that further explores the theoretical concepts introduced in the lecture and applies them to a concrete dataset.Content: The students will choose a network concept, show its application to a real world dataset and implement it in a Virtual Reality platform. The results will be presented to the course participants.Methods: Presentations and discussion of the project and the chosen approaches; independent work, implementation and documentation in exchange and discussion with a project advisor.
Assessment and permitted materials
The students will present their projects at three separate occasions to the audience of the other participants. A first presentation at the beginning of the semester outlines the planned project and steps towards its implementation. A second presentation in the middle of the semester shows the current progress. At the end of the semester there will be a final presentation of the results. In addition, the project has to be described in a report containing an introduction to the theoretical background, a description of the used real world dataset, and a discussion of the findings. In addition, the implementation into the VR platform has to be documented.
Minimum requirements and assessment criteria
Minimum requirements: Three presentations in front of the course participants; successful realization and implementation of the project; submission of project report, code and documentation.Assessment criteria: All parts enter the grading, i.e. project presentations, realization, report and documentation.
Examination topics
All topics relevant to the specific projects.
Reading list
Will be announced during the course.
Association in the course directory
MBIV
Last modified: Tu 08.03.2022 13:29