Master Thesis
Niveau
Master's course
Learning outcomes of the courses/module
The following skills are developed in the course:
- Students can independently write a Master thesis in the field of Data Science.
- Students can independently set up and carry out a scientific project.
- Students can independently write a Master thesis in the field of Data Science.
- Students can independently set up and carry out a scientific project.
Prerequisites for the course
No prerequisites
Course content
Students independently draft a project idea for their own Master thesis, describe it in the form of an exposé and submit it to the program management for approval. Students then work on the topic and write a Master thesis, which is submitted for review.
Recommended specialist literature
PRIMARY LITERATURE:
- Franck, N. (2007): Handbuch Wissenschaftliches Arbeiten (Ed. 2), Fischer Taschenbuch Verlag, Frankfurt am Main (ISBN: 978-3596151868)
- Franck, N. (2007): Handbuch Wissenschaftliches Arbeiten (Ed. 2), Fischer Taschenbuch Verlag, Frankfurt am Main (ISBN: 978-3596151868)
Assessment methods and criteria
Master thesis
Language
English
Number of ECTS credits awarded
22
Share of e-learning in %
0
Semester hours per week
0.0
Planned teaching and learning method
The following methods are used:
- Coaching within the scope of the Master thesis preparation
- Coaching within the scope of the Master thesis preparation
Semester/trimester in which the course/module is offered
4
Name of lecturer
Prof. (FH) Dipl.-Informatiker Karsten Böhm
Academic year
Key figure of the course/module
MWA.2
Type of course/module
seminar-degree
Type of course
Compulsory
Internship(s)
none