Universität Wien FIND

Due to the COVID-19 pandemic, changes to courses and exams may be necessary at short notice (e.g. cancellation of on-site teaching and conversion to online exams). Register for courses/exams via u:space, find out about the current status on u:find and on the moodle learning platform.

Further information about on-site teaching and access tests can be found at https://studieren.univie.ac.at/en/info.

Warning! The directory is not yet complete and will be amended until the beginning of the term.

053631 LP Data Analysis Project (2021W)

Continuous assessment of course work
MIXED

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. 25 participants
Language: English

Lecturers

Classes

In order to take part in the course, you have to register in u:space.
Then, we will need additional information to match you to an appropriate project. Once you have been assigned to a project, you will be accepted into the course.

We need a formal project application from you to match you to an appropriate project ***due 10. September***. You will find the corresponding form in Moodle at https://moodle.univie.ac.at/mod/resource/view.php?id=9465908.

You need to email this completed form to dsprojectunivie@gmail.com. Please use the subject line "W2021 Application - {Your name}".

Only students who signed up for the class in univis/u:space are allowed to take the class. No exceptions possible.


Information

Aims, contents and method of the course

In the course of a data analysis project, students acquire the ability to solve data science projects using the methods and techniques that the students have already learned during their studies. The range of possible project topics is quite broad, ranging from theoretical questions to applied topics with a potential industry partnership. Each project should be targeted at groups of 1-4 students, who will work on the project for the full semester, in addition to taking other classes. Each project will be supervised by our teaching staff, sometimes in cooperation with an industry partner. Common sessions and meetings will be arranged and agreed upon with the respective supervisor/s.

We are planning a joint "Data Science Day" at the beginning of summer semester 2022, 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 January.

Each project will consist of an implementation part (25%), documentation part (25%), presentation/poster part (25%), and participation part (25%) – to be specified by the particular project supervisor/s.

Minimum requirements and assessment criteria

The project must be completed by the end of January. To pass, the average grade based on above examinations must be at least sufficient / 4.0.

Examination topics

To be determined by project supervisors.

Reading list

To be determined by project supervisors.

Association in the course directory

Last modified: We 22.09.2021 17:08