Data Science

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At a glance

Faculty

Electrical engineering and computer science

Academic degree

Master of Science (M.Sc.)

Form of study

Consecutive full-time Master’s degree

Standard period of study

3 semesters (incl. Master’s thesis), 90 ECTS

Place of study

Coburg, Friedrich-Streib Campus

Language of instruction

predominantly German

Special feature

In principle, it is also possible to work close to home at the same time, although this may result in an extension of the course by one or two semesters.

Start of studies

Winter semester (October 01); summer semester (March 15)

Admission requirements

– A completed university degree of at least seven semesters (210 ECTS credits) in a Bachelor’s or Diplom degree program at a German university or another
equivalent degree, including a practical semester of at least 25 ECTS credits.
– Proven knowledge in the field of mathematics/statistics amounting to at least 14 ECTS credits and in the field of computer science amounting to at least 14 ECTS credits.
– If English is not a native language, knowledge of English at level B2 according to the Common European Framework of Reference for Languages (CEFR).

Semester abroad

Possible as a theoretical or practical semester

Accreditation

is accredited

Registration

from 02.05.
until 30.09. (for the winter semester) from 15.11.
until 15.02.
(for the summer semester)

Registration information

Profile of the Master's program

This Master’s degree program gives you, as a Bachelor’s graduate from various fields, the chance to expand your knowledge in areas such as mechanical engineering or automation technology with modern IT skills. Data science is about gaining valuable knowledge from data and deriving meaningful recommendations for action. This skill is becoming increasingly important, especially in the digital world, where IT has long been more than just support for business processes – it is part of the products and business models themselves. Your success depends more and more on how well you can analyze and use data. If you find technology, mathematics and data analysis exciting, additional training in data science could be just the thing for you. This Master’s degree will not only qualify you for management roles, but also for scientific activities in research and development.

What we value

Study internationally

Students at Coburg University of Applied Sciences have the opportunity to complete a study or practical semester abroad. To this end, Coburg University of applied sciences and arts maintains relationships with partner universities abroad.
Further information is available from the university’s Study Abroad service.

Combination of research and practice

In research, Master’s students can participate in ongoing research projects. We have contacts and joint projects with many small and large companies in Bavaria and beyond. The focus project in the second semester is precisely about implementing a data-driven project from practice.

Specialists for the data-driven world

The Master’s degree program in Data Science at Coburg University of Applied Sciences prepares specialists for the challenges of a data-driven world and opens up attractive career options. There is a high demand for data scientists who can analyze large amounts of data and support business decisions. The program offers diverse career opportunities and enables professional growth, especially for professionals with an industry-specific background. Working as a data scientist is challenging and interesting, requiring critical thinking and creativity. Data science plays a growing role in everyday life and offers attractive salaries.

Course content and schedule

The Master’s degree program in Data Science at Coburg University of Applied Sciences offers intensive supervision and small groups of students with different backgrounds. It includes practically relevant and scientifically sound topics as well as numerous opportunities for project work and Master’s theses. Core contents:

Computer science basics: tools and programming for data science, data management, big data and cloud computing
Mathematics and statistics: mathematics, multivariate statistics, visualization
Specialization: Data Mining, Deep Learning
Application: Seminar and project work
Reflection: Ethics of AI, privacy and data protection, digital transformation

Procedure:

Individual mentoring: “Interdisciplinary perspectives and study planning” module to support study and career planning
First two semesters: academic modules, project work, interdisciplinary modules
Third semester: Master’s thesis

The module handbook provides information on the content of the individual modules. The study and examination regulations form the legal basis of the degree program. Questions about the content of the degree course will be answered by the course director Prof. Dr. Thomas Wieland.