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053631 LP Data Analysis Project (2022W)
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 We 14.09.2022 09:00 to We 21.09.2022 09:00
- Deregistration possible until Fr 14.10.2022 23:59
Details
max. 25 participants
Language: English
Lecturers
- Drew Dimmery
- Ludwig Maximilian Breuer
- Jan Fabian Ehmke
- Steffen Elting
- Philipp Grohs
- Barbara Heinisch
- Laura Koesten
- Rico Kötschau
- Lukas Liehr
- Torsten Möller
- Arndt Niebisch
- Claudia Plant
- Nina Rastinger
- Claudia Resch
- Simon Rittel
- Benjamin Roth
- Anastasiia Sedova
- Sebastian Tschiatschek
Classes
Currently no class schedule is known.
Information
Aims, contents and method of the course
In the course of a data analysis project, students acquire the ability to solve data science projects using the methods and techniques that the students have already learned during their studies. The range of possible project topics is quite broad, ranging from theoretical questions to applied topics with a potential industry partnership. Each project should be targeted at groups of 1-4 students, who will work on the project for the full semester, in addition to taking other classes. Each project will be supervised by our teaching staff, sometimes in cooperation with an industry partner. Common sessions and meetings will be arranged and agreed upon with the respective supervisor/s.We are planning a joint "Data Science Day" at the beginning of next term, in which the students present their work in a poster session to a broader audience including first and second semester students of the Data Science programs.
Assessment and permitted materials
The project must be completed by the end of the term.Each project will consist of an implementation part (25%), documentation part (25%), presentation/poster part (25%), and participation part (25%) – to be specified by the particular project supervisor/s.
Minimum requirements and assessment criteria
The project must be completed by the end of term. To pass, the average grade based on above examinations must be at least sufficient / 4.0.
Examination topics
To be determined by project supervisors.
Reading list
To be determined by project supervisors.
Association in the course directory
Last modified: Th 02.02.2023 12:28