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B.Sc. Data Science

This bachelor program provides in-depth instruction in information technology, with optional modules in the scope of data analysis as well as basic education in mathematics and statistics. The degree enables entry into professions in business, administration and science in which methods of information technology and statistics are used to analyze big data (large, heterogeneous data sets), as well as qualifying the learner for a master’s program in data science, computer science and mathematics. Students who have successfully completed this B.Sc. program are, in particular, able to successfully manage relevant, practical problems involving the analysis of heterogeneous and large volumes of data using IT processing methods, tools and systems working within legal ramifications and implementing solutions within the context of the projects.

The B.Sc. Data Science program is comprised of modules (What are modules?) from the fields of Computer Science and Mathematics. The following table provides an overview of the modules to be completed throughout the course of study according to their allocation to academic disciplines in terms of content. The fundamentals are taught in the basic modules, while the advanced modules take the content further, and the practical modules provide students the opportunity to practice applying what they have learned. The elective modules can be chosen based on individual interests. Further information on the study program can be found at the German program web page, in the Study and Examination Regulations (in German only) and the current module guide.

Basic Modules in Computer Science   36
   Object-oriented Programming  
        Objektorientierte Programmierung
R 9
   Algorithms and Data Structures
        Algorithmen und Datenstrukturen
R 9
   Technical Computer Science
        Technische Informatik
R 9
   System Software and Computer Communication
        Systemsoftware und Rechnerkommunikation    
R 9
Advanced Modules in Computer Science   36
   Software Engineering
R 6
   Database Systems
R 9
   Efficient Algorithms
        Effiziente Algorithmen
R 9
   Machine Learning
        Maschinelles Lernen
R 9
   Selected Topics in Computer Science / Data Science (Seminar) R 3
Practical Modules
   Programming Lab
R 6
   Software Lab
R 6
   Advanced Software Lab for Big Data
        Fortgeschrittenenpraktikum für große Daten
R 6
   Internship Stochastics
        Praktikum zur Stochastik
R 6
Basic Modules in Mathematics   18
   Basic Linear Algebra
        Grundlagen der linearen Algebra
R 9
   Basic Real Analysis
        Grundlagen der Analysis
R 9
Advanced Modules in Mathematics   27
   Basic of Advanced Mathematics
        Grundlagen der Höheren Mathematik
R 9
R 9
   Elementary Stochastics
        Elementare Stochastik
R 9
Electives in Mathematics   15-18
   Eligible modules according to the module guide E 15-18
Electives in Computer Sciences
   Eligible modules according to the module guide E 9-12
Final Module
   Bachelor Thesis
R 12
Sum   180

(R=Required module, E=Elective module)