Universität Wien FIND

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040309 VU Doing Data Science (MA) (2021S)

6.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
REMOTE

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.

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. 40 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

This course will be taught fully digitally. It will consist of a mixture of live online meetings (including Q&A sessions and tutorials) and recorded videos. Students will have to present their work online and hence need a microphone/webcam. For more details, see the schedule in Moodle.

Tuesday 02.03. 13:15 - 14:45 Digital
Wednesday 03.03. 15:00 - 16:30 Digital
Tuesday 09.03. 13:15 - 14:45 Digital
Wednesday 10.03. 15:00 - 16:30 Digital
Tuesday 16.03. 13:15 - 14:45 Digital
Wednesday 17.03. 15:00 - 16:30 Digital
Tuesday 23.03. 13:15 - 14:45 Digital
Wednesday 24.03. 15:00 - 16:30 Digital
Tuesday 13.04. 13:15 - 14:45 Digital
Wednesday 14.04. 15:00 - 16:30 Digital
Tuesday 20.04. 13:15 - 14:45 Digital
Wednesday 21.04. 15:00 - 16:30 Digital
Tuesday 27.04. 13:15 - 14:45 Digital
Wednesday 28.04. 15:00 - 16:30 Digital
Tuesday 04.05. 13:15 - 14:45 Digital
Wednesday 05.05. 15:00 - 16:30 Digital
Tuesday 11.05. 13:15 - 14:45 Digital
Wednesday 12.05. 15:00 - 16:30 Digital
Tuesday 18.05. 13:15 - 14:45 Digital
Wednesday 19.05. 15:00 - 16:30 Digital
Wednesday 26.05. 15:00 - 16:30 Digital
Tuesday 01.06. 13:15 - 14:45 Digital
Wednesday 02.06. 15:00 - 16:30 Digital
Tuesday 08.06. 13:15 - 14:45 Digital
Wednesday 09.06. 15:00 - 16:30 Digital
Tuesday 15.06. 13:15 - 14:45 Digital
Wednesday 16.06. 15:00 - 16:30 Digital
Tuesday 22.06. 13:15 - 14:45 Digital
Wednesday 23.06. 15:00 - 16:30 Digital
Tuesday 29.06. 13:15 - 14:45 Digital
Wednesday 30.06. 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%): March 24, 15:00
Final test (30%): May 12, 15:00
Project work (40%): Final presentations: June 29

Minimum requirements and assessment criteria

Two of three examinations 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 21.04.2021 11:25