Universität Wien FIND

053640 SE Master's Seminar (2022S)

Continuous assessment of course work


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


max. 25 participants
Language: English



Currently no class schedule is known.


Aims, contents and method of the course

The aim is to conduct a data-driven project in the field of Data Science. Based on the experience gained during the implementation of the project students should learn to carry out Data Science projects on their own. The aim is also to combine previously acquired knowledge from the various courses during the study.

Assessment and permitted materials

A detailed specification of the requirements, as well as a guide and notes on the implementation of the project will be announced at the beginning of the course together with the assignment of the project topics.

Minimum requirements and assessment criteria

Prerequisites for the Masterseminar are the successful completion of:
- Introduction to Machine Learning
- Statistics for Data Science
- Mathematics for Data Science
- Optimization methods for Data Science
- Mining Massive Data
- Visual and Exploratory Analysis
- Doing Data Science
- Ethical and Legal Issues
- Data Analysis Project and Seminar

Examination topics

The goal is to make progress in your master thesis. You will be judged by the milestones you and your supervisor will agree upon.

Reading list

Literature and further details are announced by the supervisor in the course.

Association in the course directory

Last modified: We 16.03.2022 09:07