Universität Wien FIND

Due to the COVID-19 pandemic, changes to courses and exams may be necessary at short notice. Inform yourself about the current status on u:find and check your e-mails regularly. Registration is mandatory for courses and exams. Wearing a FFP2 face mask and a valid evidence of being tested, vaccinated or have recovered from an infection are mandatory on site.

Please read the information on studieren.univie.ac.at/en/info.

040172 VU Doing Data Science (MA) (2021W)

6.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
MIXED

The course language is English.

Only students who signed up for the class in univis/u:space are allowed to take the class (that means, that you have to at least be on the waiting list if you want to take this class). No exceptions possible.
Tu 19.10. 15:00-16:30 Digital

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).

Details

max. 80 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

This class will be offered in hybrid form. As long as allowed, we will offer one on-site appointment per week (see schedule). To attend, proof of 3G (vaccinated/tested/recovered) and registration will be necessary. All appointments (online and on-site) will be streamed through Moodle/BigBlueButton.

Tuesday 05.10. 15:00 - 16:30 Digital
Tuesday 12.10. 15:00 - 16:30 Digital
Wednesday 13.10. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 13.10. 15:00 - 16:30 Digital
Wednesday 20.10. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 20.10. 15:00 - 16:30 Digital
Wednesday 27.10. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 27.10. 15:00 - 16:30 Digital
Wednesday 03.11. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 03.11. 15:00 - 16:30 Digital
Tuesday 09.11. 15:00 - 16:30 Digital
Wednesday 10.11. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 10.11. 15:00 - 16:30 Digital
Tuesday 16.11. 15:00 - 16:30 Digital
Wednesday 17.11. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 17.11. 15:00 - 16:30 Digital
Tuesday 23.11. 15:00 - 16:30 Digital
Wednesday 24.11. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 24.11. 15:00 - 16:30 Digital
Tuesday 30.11. 15:00 - 16:30 Digital
Wednesday 01.12. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 01.12. 15:00 - 16:30 Digital
Tuesday 07.12. 15:00 - 16:30 Digital
Tuesday 14.12. 15:00 - 16:30 Digital
Wednesday 15.12. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 15.12. 15:00 - 16:30 Digital
Tuesday 11.01. 15:00 - 16:30 Digital
Wednesday 12.01. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 12.01. 15:00 - 16:30 Digital
Tuesday 18.01. 15:00 - 16:30 Digital
Wednesday 19.01. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 19.01. 15:00 - 16:30 Digital
Tuesday 25.01. 15:00 - 16:30 Digital
Wednesday 26.01. 13:15 - 14:45 Digital
PC-Seminarraum 1, Kolingasse 14-16, OG01
Wednesday 26.01. 15:00 - 16:30 Digital

Information

Aims, contents and method of the course

This course covers the fundamentals of setting up, managing, and conducting data science projects. Students acquire knowledge of processes describing how to approach and implement data science projects. They know the particular steps of the CRISP industry-standard, learn about various cases of how to apply this to different applications (from different areas such as business, humanities, astronomy), and are able to conduct data science projects themselves.

This course consists of lectures, tutorials, showcases, and project presentations. Students will work on their own data science projects in interdisciplinary groups.

Assessment and permitted materials

Midterm test (30%): Nov 16, 15:00
Final test (30%): Dez 14, 15:00
Project work (40%): Ongoing, final presentations: Jan 18, Jan 19

Minimum requirements and assessment criteria

The midterm test and one more examination (project work / final test) must be passed individually.
For project work, attendance is mandatory, including kick-off and project presentations.

In total, 100 points can be achieved. Grades are assigned as follows:
1 (very good) • 100-90 points
2 (good) • 89-76 points
3 (satisfactory) • 75-63 points
4 (sufficient) • 62-50 points
5 (not enough) • 49-0 points

Examination topics

Midterm test/Final test: Slides and topics covered in the lectures.
Project work: topic-specific poster presentation, handout, KNIME workflow.

Reading list

See lecture

Association in the course directory

Last modified: We 29.09.2021 13:48