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053631 LP Data Analysis Project (2024W)
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 Fr 13.09.2024 09:00 to Fr 20.09.2024 09:00
- Deregistration possible until Mo 14.10.2024 23:59
Details
max. 25 participants
Language: English
Lecturers
- Andrea Tanzer
- Jeremy Bradley
- Liam Downs-Tepper
- Moritz Grosse-Wentrup
- Rebecca Josina Kahn
- Nils Morten Kriege
- Lukas Miklautz
- Jörg Mühlhans
- Arndt Niebisch
- Claudia Plant
- Nina Rastinger
- Sebastian Ratzenböck
- Simon Rittel
- Benjamin Roth
- Anastasiia Sedova
- Sebastian Tschiatschek
- Thomas J.J. Wallnig
Classes (iCal) - next class is marked with N
- Thursday 03.10. 11:30 - 13:00 Hörsaal 2, Währinger Straße 29 2.OG
Information
Aims, contents and method of the course
During a data analysis project, students acquire the ability to solve data science projects using the methods and techniques they have already learned during their studies. The range of possible project topics is quite broad, from theoretical questions to applied topics with a potential industry partnership. Most projects are for single students, with the intention that they will transform into suitable thesis projects. Sometimes, projects can be group projects for more than one student who will work together. Supervisory meetings will be arranged and agreed upon with the respective supervisor/s.We are planning a joint "Data Science Day" in May 2024, 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 (22,5%), documentation part (22,5%), presentation/poster part (22,5%), and participation part (22,5%) – to be specified by the particular project supervisor/s. In addition, we will ask you to broaden your horizons by attending a couple of research talks organized by the research network during the semester (10%).
Minimum requirements and assessment criteria
The project must be completed by the end of the term. The grading scale for the course will be:
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%
Examination topics
To be determined by project supervisors.
Reading list
To be determined by project supervisors.
Association in the course directory
Last modified: Tu 12.11.2024 12:45