Interdisciplinary Project in Data Science
Project addressing a domain-specific challenge.
The interdisciplinary project is part of the corresponding module in the Data Science curriculum and forms a content block together with the lecture series 194.046 Interdisciplinary Lecture Series on Data Science, as well as the course 194.047 Domain-Specific Lectures in Data Science.In principle, all topics/disciplines presented in the lecture series 194.046 Interdisciplinary Lecture Series on Data Science in previous years are available for the project, with the respective lecturers as main supervisors.The domain-specific lecture, to be selected from the list available in TISS, provides the basic skills needed for the work in the corresponding interdisciplinary project. Therefore, that course should ideally be completed before or possibly during the work on this project.
Steps for the Interdisciplinary Project in Data Science
1. Select a main supervisor for the project
- Usually not from the Faculty of Informatics (or Mathematics)
- Not necessarily from the TU Wien
- All presenters of the associated Lecture Series (194.046) of the past years (as listed in the TUWEL course of the lecture series) are available to act as main supervisor for the project.
2. Discuss the project with the selected supervisor, agree on a 1 to 2-page proposal document and identify the corresponding domain-specific lecture in data science (from the list available for course 194.068)
3. Select a co-supervisor for the project
- Usually from the Faculty of Informatics or Mathematics
- Must be from the TU Wien
- Specifically, anybody that has lectured any of the Data Science courses (see list below)
4. Discuss the 1 to 2-page project proposal with the co-supervisor. Ensure, specifically, that the key methods covered inthe Data Science Curriculum, are referred to and will be properly applied in the project. (e.g. CRIS-DM, Experiment Design, Reproducibility, Data Science lecture specific methods)
5. Refine the project proposal until both supervisors agree and upload the final version on TUWEL
6. Do the project
7. Discuss regularly with the supervisors
8. Write the report and prepare the poster
9. Once approved by both supervisors upload the final report and the poster to TUWEL
Note that a project with the company that you are currently working for is generally not a good fit to the requirements for this inter-disciplinary project.
Potential Main Supervisors
Look at the list of lecturers of the "Domain-Specific Lectures in Data Science" over the last years.
The following people are potential co-supervisors:
Jesper Larsson Träff
Steps in the Module “DSA – Domain-Specific Aspects of Data Science”
- Attend the Interdisciplinary Lecture Series on Data Science (194.046)
- Choose an area
- Get theoretical knowledge through attending a lecture in this area (3,0/2,0 VO/VU/SE Fachspezifische Lehrveranstaltungen)
- Solve a practical problem in inter-disciplinary project work – Interdisciplinary Project in Data Science (194.060/194.047)
<p>Report on the results</p>
<p><strong></strong>If the supervisor and co-supervisor do not have the rights to issue a certificate, the supervisor or co-supervisor should send an e-mail to <a href="mailto:email@example.com" rel="nofollow">firstname.lastname@example.org</a> (with all involved people in cc) containing the final grade for the project. The certificate will then be issued in the names of the supervisor and co-supervisor (as possible given their affiliation to the TU Wien).</p>