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Master Data Science



Price on request


  • Type


  • Methodology


  • Duration

    12 Months

Data is becoming the most important asset of data-driven enterprises and plays a pivotal role in tackling the challenges of tomorrow. From the optimisation of existing production lines to the creation of new business models, data-driven decisions are at the centre of digital businesses.

About this course

Innovation springs from bright minds - our international Master programme puts you into the driver seat of your future career in Data Science. Graduates from our courses go to become technical gurus, team-leaders of successful data-science teams or value-driven masterminds who turn data into action.

Prerequisites for admission to the Data Science Master programme:

Completed undergraduate study from a public or officially recognised university/higher education institution;
Degree certification of at least “Befriedigend” [lower second equivalent];
Proof of min. one year of relevant work experience;
Proof of English skills.

TOEFL (min. 80 points) or
IELTS (min. Level 6) or
Duolingo English test (min. 51%) or
Cambridge Certificate (min. B grade overall) or
Equivalent proof
The proof must be provided before the start of the study and must not be older than two years. If English is your native language or you graduated from an English-speaking school/university, you do not have to prove your English skills.

The Master in Data Science opens the door for your career in data-driven businesses.

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  • Data science
  • Mathematics
  • Data analysis
  • Data Protection
  • Data Collection
  • Data Management
  • Statistics
  • Society
  • Machine Learning
  • Big Data Management
  • Big Data Technologies
  • IT Security
  • Model Engineering
  • Software Engineering
  • Advanced Mathematics
  • Management Information Systems
  • Advanced Statistics
  • Project
  • Project Control
  • Project Management

Course programme

1st semester
  • Data Science
  • Advanced Mathematics
  • Seminar: Data Science and Society
  • Advanced Statistics
  • Use Case and Evaluation
  • Project: Data Science Use Case

2nd semester
  • Programming with Python
  • Machine Learning
  • Deep Learning
  • Big Data Technologies
  • Electives A (Selection of one module)

3rd semester
  • IT Security and Data Protection
  • Model Engineering
  • Software Engineering for Data Intensive Sciences
  • Electives B (Selection of one course)
  • Seminar: Current Topics in Data Science

4th semester
  • Master Thesis & Colloquium

Master Data Science

Price on request