1. Semester

• Collaborative Work (5 CP)
• Introduction to Academic Work (5 CP)
• Introduction to Data Science (5 CP)
• Introduction to Programming with Python (5 CP)
• Mathematics: Analysis (5 CP)
• Statistics: Probability and Descriptive Statistics (5 CP)

2. Semester

• Database Modeling and Database Systems (5 CP)
• Intercultural and Ethical Decision-Making (5 CP)
• Mathematics: Linear Algebra (5 CP)
• Object Oriented and Functional Programming with Python (5 CP)
• Project: Build a Data Mart in SQL (5 CP)
• Statistics - Inferential Statistics (5 CP)

3. Semester

• Business Intelligence (5 CP)
• Data Science Software Engineering (5 CP)
• Machine Learning - Supervised Learning (5 CP)
• Machine Learning - Unsupervised Learning and Feature Engineering (5 CP)
• Project: Business Intelligence (5 CP)
• Project: From Model to Production (5 CP)

4. Semester

• Agile Project Management (5 CP)
• Big Data Technologies (5 CP)
• Cloud Computing (5 CP)
• Data Quality and Data Wrangling (5 CP)
• Explorative Data Analysis and Visualization (5 CP)
• Seminar: Ethical Considerations in Data Science (5 CP)

5. Semester

• Elective A (10 CP)
  • AI Specialist (10 CP, W)
  • Data Analyst (10 CP, W)
  • Data Engineer (10 CP, W)
• Elective B (10 CP)
  • Applied Sales (10 CP, W)
  • Autonomous Driving (10 CP, W)
  • International Marketing and Branding (10 CP, W)
  • Managerial Economics and Corporate Finance and Investment (10 CP, W)
  • Production Engineering, Automation and Robotics (10 CP, W)
  • Smart Factory (10 CP, W)
  • Supply Chain Management (10 CP, W)
• Neural Nets and Deep Learning (5 CP)
• Time Series Analysis (5 CP)

6. Semester

• Bachelor Thesis (10 CP)
• Elective C (10 CP)
  • Foreign Language French (10 CP, W)
  • Foreign Language German (10 CP, W)
  • Foreign Language Italian (10 CP, W)
  • Foreign Language Spanish (10 CP, W)
  • Studium Generale (10 CP, W)
• Introduction to Data Protection and Cyber Security (5 CP)
• Model Engineering (5 CP)

1. Semester

• Data Science (5 CP)
• Evaluierung und Use Case (5 CP)
• Projekt: Data Science Use Case (5 CP)
• Seminar: Data Science und Gesellschaft (5 CP)
• Weiterführende Mathematik (5 CP)
• Weiterführende Statistik (5 CP)

2. Semester

• Big-Data-Technologien (5 CP)
• Deep Learning (5 CP)
• Machine Learning (5 CP)
• Programmieren mit Python (5 CP)
• Wahlpflichtmodul A (10 CP, W)
  • Business Analyst (10 CP, W)
  • Data Engineer (10 CP, W)
  • Data Science Specialist (10 CP, W)
  • Technical Project Lead (10 CP, W)

3. Semester

• Fallstudie: Model Engineering (5 CP)
• IT-Sicherheit und Datenschutz (5 CP)
• Seminar: Aktuelle Themen im Data Science (5 CP)
• Software Engineering für Datenwissenschaften (5 CP)
• Wahlpflichtmodul B (10 CP, W)
  • Angewandtes Autonomes Fahren (10 CP, W)
  • Automatisierungstechnik und Internet of Things (10 CP, W)
  • Cognitive Computing (10 CP, W)
  • Global Branding und Sales (10 CP, W)
  • Innovate and Change (10 CP, W)
  • Konsumentenverhalten und Internationales Marketing (10 CP, W)
  • Management (10 CP, W)
  • Self Learning Systems (10 CP, W)
  • Strategisches Finanzmanagement (10 CP, W)

4. Semester

• Masterarbeit (30 CP)