Digital transformation creates opportunities across product development, production, marketing, customer relationship management and sales—but it also produces vast amounts of data and new practical challenges. This Master’s programme trains students to go beyond pure statistical analysis and IT pipelines: graduates learn to turn data into actionable insight, communicate findings effectively, and apply solutions in organisational contexts. Emphasis is placed on ethical, legal and business perspectives so that data scientists can address problems strategically and implement results with strong communication skills.
The course is explicitly interdisciplinary, combining topics from business informatics, mathematics and statistics, business administration and marketing, as well as media, law and communication science. Designed as a part-time, international Master’s degree within Department 4 (Economics), it fills the gap between single-discipline training and the broad skill set employers now demand. Teaching is delivered in English and the programme is offered in cooperation with the High‑tech Business & Entrepreneurship Group of the University of Twente (Netherlands).
This part-time, practice-focused Master's programme is delivered entirely in English (minimum B2 level) and awards a Master of Science degree. It runs over four semesters—including the final thesis—and requires a total of 90 credit points. Teaching includes 380 hours of face-to-face instruction delivered in compact blocks of four and a half days, and a practical project is completed alongside coursework to ensure applied experience.
The curriculum covers core data science skills and supporting professional competencies. Core technical topics include introduction to data science and programming systems, data management, and data analytics. The programme also addresses IT management, IT security, ethical and legal aspects of data use, plus communication and social media in data contexts. In addition, students work on self-management and leadership, a supervised practical phase/project, and a domain-focused module on application areas. Assessments mix written exams, case studies, presentations, essays, and project deliverables to evaluate both technical proficiency and real-world problem solving.
Graduates will leave with assessed experience across technical, managerial and communication dimensions of data science, demonstrated through a practical project and a research-led master’s thesis (see bullets below for exact requirements and assessment formats).
Key facts and assessment requirements
Module assessments
PDF download available for full curriculum details.
You must hold a first university degree corresponding to at least 180 ECTS credits. This is the core academic entry requirement for the Master’s program.
For most applicants, 180 ECTS is equivalent to a three‑year bachelor’s degree. If your home institution uses a different credit system or naming convention, the admissions office will assess whether your qualification is comparable to the 180 ECTS threshold.
Winter Semester (International)
15 September 2025
Winter Semester (EU/EEA)
15 September 2025
Graduates are well positioned for roles that bridge technical data work and business decision‑making — for example in analytics, business intelligence, data‑driven marketing, product development, IT management and data governance. The programme’s combination of technical, legal/ethical and communication training prepares alumni to coordinate cross‑functional teams and to translate analytical results into strategic action.
Because the course is structured for working professionals and emphasises practical projects, it is especially suitable for those aiming to upskill within their current organisation or to move into applied data roles in industry, consulting or public institutions.
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University of Regensburg — Regensburg
University of Bonn — Bonn
Brandenburg University of Technology Cottbus-Senftenberg — Cottbus