Master's Thesis
Niveau
Master's program
Learning outcomes of the courses/module
The participants:
• can independently write a master's thesis in the field of data science
• can independently set up and carry out an academic project
• can independently write a master's thesis in the field of data science
• can independently set up and carry out an academic project
Prerequisites for the course
No prerequisites
Course content
Students independently design a project idea for their own master's thesis, describe it in the form of an exposé and submit it to the program management for approval. The students then work on the topic and write a master's thesis, which is submitted for assessment.
Recommended specialist literature
- Poser, H. (2001): Wissenschaftstheorie. Eine philosophische Einführung (Ed. 1), Reclam, Dithingen (ISBN: 978-3150181256)
- Franck, N. (2017): Handbuch Wissenschaftliches Arbeiten (Ed. 3), Fischer Taschenbuch Verlag, Frankfurt am Main (ISBN: 978-3825247485)
- Franck, N. (2017): Handbuch Wissenschaftliches Arbeiten (Ed. 3), Fischer Taschenbuch Verlag, Frankfurt am Main (ISBN: 978-3825247485)
Assessment methods and criteria
Master's thesis
Language
German
Number of ECTS credits awarded
22
Semester hours per week
Planned teaching and learning method
The following methods are used:
- Coaching during the preparation of the master's thesis
- Coaching during the preparation of the master's thesis
Semester/trimester in which the course/module is offered
4