Main Content
Does the Data Science Degree Fit Me and My Expectations?
Prior Knowledge
For a successful master's program in Data Science, you should have a sound knowledge of the contents taught in the bachelor's program. Besides a completed bachelor's degree in Data Science, a bachelor's degree in Mathematics or Computer Science may also qualify you for a master's degree in Data Science; in this case, admission may be subject to conditions. For more information, please refer to the brief description of the program.
For writing papers and project work, knowledge of the text typesetting program LaTeX is an advantage.
Traits and Interests
Inhalt ausklappen Inhalt einklappen Excitement About Data Analysis, Analytical Thinking and Scientific Research-Related Work
Since the study of Data Science deals with issues from areas of computer science as well as mathematics, you should generally be interested in both disciplines. It does not matter which areas of the respective specialization you like best. However, you should be prepared to deal scientifically with the questions and problems in the respective field.
Inhalt ausklappen Inhalt einklappen Logic and Abstraction Skills
In addition to the ability to think logically, you should have the ability to abstract in order to apply discovered approaches to analogous problems.
Inhalt ausklappen Inhalt einklappen Familiarity With Computers and Programming Languages
The focus of the study program is on computer science. During your studies, you will learn to design efficient algorithms for data analytic problems and to implement them in distributed programs. Therefore, you should be interested in and enjoy distributed programming.
Inhalt ausklappen Inhalt einklappen Self-Organization, Ambition and High Frustration Tolerance
In the master's program, you will be confronted with complex problems and tasks whose solution is not always immediately obvious. You should therefore bring with you the endurance you have already trained in your bachelor's studies and not be discouraged by difficult questions.