Studienplan

Data Science and Analytics

Bachelorstudiengang / Vollzeit

1. Semester

Course Type SWS ECTS
Statistics and Mathematics
Algebra and Discrete Mathematics
Algebra and Discrete Mathematics – Theory VO 2 3
Algebra and Discrete Mathematics – Exercise UE 1 2
Introduction to Probability & Statistics
Introduction to Probability & Statistics – Theory VO 2 3
Introduction to Probability & Statistics with Excel and R – Exercise UE 1 2
Software Process
Introduction to Programming I
Introduction to Programming I (Python) – Theory VO 1 2
Introduction to Programming I (Python) – Exercise UE 2 2
Software Engineering Processes
Software Engineering Processes - Theory VO 2 2
Software Engineering Processes – Exercise UE 1 1
Data Generation, Data Management and Data Analysis
Fundamentals Data Science
Introduction to Data Science and Digital Trends VO 2 3
Business and Economics
General Business Administration VO 2 3
Project Management ILV 2 2
Law and Ethics
IT Law, Data and Privacy Law VO 2 3
Reflections on Data Science, Law and Ethics TU 1 1
Language and Social Skills
Contextual English I WK 1 1

2. Semester

Course Type SWS ECTS
Statistics and Mathematics
Analysis ILV 3 5
Inferential Statistics ILV 3 5
Software Process
Algorithms and Methods
Algorithmics and Data Structures (Advanced Python) ILV 3 4
Introduction to Programming II
Introduction to Programming II (R) ILV 3 4
Data Generation, Data Management and Data Analysis
Data Analysis
Database and Database Management ILV 2 3
Data Visualisation
Visual Perception and Information Design VO 2 3
Law and Ethics
Reflections on Data Science, Law and Ethics TU 1 1
Research and Scientific Working
Research Methods I PS 2 3
Language and Social Skills
Communication and Presentation Skills WK 1 1
Contextual English II WK 1 1

3. Semester

Course Type SWS ECTS
Statistics and Mathematics
Advanced Statistics ILV 2 4
Software Process
Algorithms and Methods
Data Analysis and Methods (Advanced R) ILV 3 4
Data Generation, Data Management and Data Analysis
Data Analysis
Data Mining ILV 2 3
Data Acquisition
User Data VO 2 3
Data Visualisation
Data and Visualisation Types VO 2 3
Business and Economics
Market Research ILV 2 3
Managerial Economics VO 2 3
Business Models VO 2 2
Law and Ethics
Reflections on Data Science, Law and Ethics TU 1 1
Language and Social Skills
Writing Skills (Reports) WK 1 2
Creative Thinking WK 2 2

4. Semester

Course Type SWS ECTS
Statistics and Mathematics
Model Driven Development
Model Driven Development – Theory VO 2 2
Model Driven Development – Exercise UE 1 2
Data Generation, Data Management and Data Analysis
Data Analysis
Large Scale and Big Data Analysis ILV 3 3
Artificial Intelligence (Analysis 2)
Machine Learning ILV 3 4
Analytics ILV 3 4
Data Acquisition
Machine Data ILV 2 3
Content Analytics ILV 3 4
Data Visualisation
Interactive Data Visualisation ILV 2 4
Business and Economics
Business Intelligence ILV 2 3
Law and Ethics
Reflections on Data Science, Law and Ethics TU 1 1

5. Semester

Course Type SWS ECTS
Data Generation, Data Management and Data Analysis
Fundamentals Data Science
IT and Cybersecurity VO 2 3
Digital Trends and Technologies WK 2 3
Domains Knowledge
Current Domains Knowledge WK 2 3
Applied Interdisciplinary LAB WK 2 6
Business and Economics
Economics of Networks VO 2 3
Financial Applications ILV 2 4
Information and Security Management VO 2 3
Law and Ethics
Reflections on Data Science, Law and Ethics TU 1 1
Research and Scientific Working
Research Methods II SE 2 3
Language and Social Skills
Intercultural Competences WK 1 1

6. Semester

Course Type SWS ECTS
Research and Scientific Working
Bachelor Seminar and Bachelor Paper BASE 1 8
Bachelor Exam AP 0 2
Practical Training Semester
Practical Training (20 weeks á 32 hours) BOPR 0 20


Curriculum effective from: WS19/20