Universität Wien

960019 VU Basics of IT and Data Science (2023W)

3.00 ECTS (2.00 SWS), Zertifikatskurse
Continuous assessment of course work
REMOTE

Hierbei handelt es sich um ein kostenpflichtiges Angebot der Universitätslehrgänge/Zertifikatskurse des Postgraduate Center. Bitte beachten Sie, dass für die Teilnahme eine Zulassung zum Universitätslehrgang/Zertifikatskurs erforderlich ist. Weitere Informationen zu den Angeboten des Postgraduate Center finden Sie unter: https://www.postgraduatecenter.at/

Details

Language: German

Lecturers

Classes

Currently no class schedule is known.

Information

Aims, contents and method of the course

This module covers the fundamentals of IT applications and data science in terms of their potential in relation to data-driven research. After this module the students will be able to

Understand the most important concepts in Data Science, Machine Learning and Database Systems
Describe the basic concepts of programming
Know the basics of structured programming (e.g. data types, control structures, subroutines, functions …)
Describe the most important programming languages and their different aspects
Choose a suitable Integrated Development Environment (IDE) for developing own programs
Work in the Unix Shell using the most important commands for the file system and data files
Use Git/GitHub/GitLab for setting up own projects, share them and find other projects
Develop small programs in Python using basic data types, control structures, functions and software libraries

Assessment and permitted materials

The assessment consists of a multiple-choice quiz in Moodle and practical exercises. Participants are expected to study set reading materials and the contents covered in class in order to successfully complete several assignments using the tools introduced in the module. Further information will be provided in Moodle well in advance.

Minimum requirements and assessment criteria

Regular attendance and an avarage grade of the test and the assignments
The grading key for each assignment and the overall grade:
Grading key:
1 (excellent) 25-23 points
2 (good) 22.9-20 points
3 (satisfactory) 19.9-16 points
4 (sufficient) 15.9-13 points
5 (insufficient) < 13 points

Examination topics

Participants are expected to study set reading materials and the contents covered in class in order to successfully complete several assignments using the tools introduced in the module. Further information will be provided in Moodle well in advance.

Reading list

The reading list including relevant journal articles and book chapters will be assigned in connection with the session topics and made available through Moodle.

Association in the course directory

Last modified: We 07.08.2024 14:46