Overview of modules taught in English

Semester	Level	ECTS	Level
fall	basic	3	Object Oriented Programming 1
fall	basic	3	Fundamentals of Mathematics for Computer Science
fall	basic	3	Requirements Engineering
fall	basic	6	Project 3 Computer Science
fall	basic	3	Project Management
fall	basic	3	Software Development Process
fall	int	3	Computer Graphics
fall	int	3	Design Patterns
fall	int	3	E-Solutions
fall	int	3	Marketing and Product Management
fall	int	3	Media Computing
fall	int	3	Software Construction
fall	int	3	Software Testing and Quality Management
fall	adv	6	Project 5
	adv		iPOLE
fall	adv	12	Project 6 / Bachelor-Thesis
fall	adv	3	Web Frameworks
fall	adv	3	Game Design and Development
fall	basic	3	Design Patterns
fall	adv	3	Simulation & Agents
fall	int	3	Introduction to Perl for Programmers
spring	basic	6	Project 4 Computer Science
spring	basic	3	Requirements Engineering
spring	int	3	Discrete Stochastics
spring	int	3	Mathematics for Data Communication
spring	int	3	Object Oriented Programming 2
spring	int	3	Current Management Topics by MOOCs
spring	int	3	Software Construction
spring	adv	3	Game Design and Development
spring	adv	3	Visualising Information
spring	adv	3	Machine Learning (Online Course)
spring	adv	6	Project 5 Computer Science
spring	adv	6	iPOLE
spring	adv	12	Project 6 Computer Science/ Bachelor-Thesis
spring	int	3	Introduction to Theoretical Computer Science
spring	adv	3	Visualising Information

In the BSc Data Science program, there are no traditional face to face lectures. Instead, you will get access to an online library with learning videos, texts and assignments to acquire the knowledge of a Data Scientist. As a self-directed learner, you decide when you learn - at home or on campus. You will be supported by an English-speaking coach who will provide you with the necessary study materials in English.

Semester	Level	ECTS	Module
spring	basic	3	Foundation in Mathematics (mag)
fall	basic	2	Information Literacy (ink)
fall&spring	basic	3	Foundation in Databases (gdb)
fall&spring	basic	3	Probability Modelling (wer)
fall&spring	basic	1	Foundation in Data Science (gds)
fall&spring	basic	3	Foundation in Data Visualisation (gdv)
fall&spring	basic	2	Interactive Visualisation (ivi)
fall&spring	basic	3	Foundation in Writing (gsr)
fall&spring	basic	3	Presenting (pra)
fall&spring	basic	2	Effective Argumentation (wiar)
fall&spring	basic	2	Digital Communication (dko)
fall&spring	basic	2	Data-Driven Business Models (dgm)
fall&spring	basic	2	Learning Workshop (lwk)
fall&spring	basic	2	Selfmanagement (smg)
fall&spring	basic	3	Digital Portfolio (dpo)
fall&spring	basic	3	Introduction to Business Administration (bwg)
fall&spring	basic	2	Participative Events (pvd)
fall&spring	int	3	Software Construction (sko)
fall&spring	int	4	Data Wrangling (daw)
fall&spring	int	3	Database Design and Implementation (ddi)
fall&spring	int	2	Web Data Collection (wdb)
fall&spring	int	2	Data Collection IoT (idb)
fall&spring	int	3	Foundation in Image and Signal Processing (gbsv)
fall&spring	int	6	Foundation in Machine Learning (gml)
fall&spring	int	2	Visual Analytics (van)
fall&spring	int	4	Natural Language Processing (npr)
fall&spring	int	2	Data Storytelling (std)
fall&spring	int	3	Advanced Writing (vsr)
fall&spring	int	2	Ethical Reflection (ere)
fall&spring	int	2	Ethical Implementation (eim)
fall&spring	int	3	Digital Entrepreneurship & Innovation (dei)
fall&spring	int	2	Knowledge Management (wima)
fall&spring	int	2	Design Thinking for Data Scientists (dtds)
fall&spring	int	2	Intercultural Competency (iko)
fall&spring	int	4	Recommender Systems (rsy)
fall&spring	int	4	Applied Machine Learning (aml)
fall&spring	int	2	Personal Knowledge Management (pwm)
fall&spring	int	2	Leadership (lds)
fall&spring	adv	3	Stochastic Processes and Time Series (spz)
fall&spring	adv	3	Efficient Machine Learning Algorithms (eml)
fall&spring	adv	3	Cloud Infrastructure and Computing (cic)
fall&spring	adv	4	High Performance Computing (hpc)
fall&spring	adv	4	Deep Learning (del)
fall&spring	adv	3	Deep Learning on Image and Signal (dlbs)
fall&spring	adv	2	Advanced Topics in Machine Learning (fml)
fall&spring	adv	2	Actively Shaping your Career Path (lage)

Semester	Level	ECTS	Module
fall	int	3	Analogue Electronics
fall	int	3	Modelling of Dynamic Systems
fall	int	3	Thermodynamics
fall	int	6	Project 3 Electrical and Information Technology
fall	adv	3	Control Design of Dynamical Systems
spring	int	3	Control Engineering – Fundamentals
spring	int	6	Project 4 Electrical and Information Technology
spring	adv	3	Smart Power Engineering
spring	adv	3	Embedded Systems Software Design
spring	adv	3	Analog Circuits for Embedded Systems
fall or spring	adv	6	Project 5 Electrical and Information Technology
fall or spring	adv	12	Project 6 Electrical and Information Technology (Bachelor Thesis)

Semester	Level	ECTS	Module
fall&spring	B1 - B2	2	English Language*
fall&spring	C1 - C2	2	English Electives*
fall&spring	basic	2	Intercultural Awareness
fall&spring	basic	2	Business Accounting for Strategic Management
fall&spring	basic	2	South Africa - Present and Past
fall&spring	A1 - A2	2	German language for exchange students
fall&spring	basic	2	International Business and Human Rights / Exploring the Links Between Business Operations and Human Rights

* Admission to English Language E1-E4 and English Electives will be based on a Placement Test.

Overview of modules taught in English

Degree Programmes

Contact