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Who is the Master Data Science at FernUniversität Hagen suitable for?
The degree programme is designed for professionals and academics who already hold a first university degree, especially in the fields of mathematics, computer science or related disciplines, and who wish to expand their competencies in the field of data science. It also addresses specialists from other disciplines with an analytical background who are confronted with data-based issues, data mining, machine learning or the analysis of large data sets in their work environment. The distance learning course is particularly suitable for individuals who want to organise their further education flexibly alongside their job and wish to thoroughly learn the complete Data Science Life Cycle at an academic level.
Formal admission requirements for the degree programme
To enrol in the Master Data Science (M.Sc.) at FernUniversität Hagen, you need:
- A first professional qualifying university degree (Bachelor, Diplom or equivalent) with at least 180 ECTS credits.
- The degree should preferably have been obtained in mathematics, computer science or a related discipline.
- Proof of basic knowledge in mathematics, statistics, programming and ideally in data structures and algorithms is expected. A lateral entry from other subjects is possible, provided that the corresponding basics can be demonstrated.
- The formal verification of the professional and content-related requirements is carried out by the Faculty of Mathematics and Computer Science as part of the enrolment process.
- In case of doubt, an individual assessment, possibly combined with conditions (e.g. the completion of certain modules), may be required.
Personal requirements and recommended experience:
- Analytical thinking, structured problem-solving behaviour and a strong interest in quantitative methods.
- Willingness to engage with complex mathematical, statistical and IT-specific content.
- Solid prior knowledge in statistics, experience with at least one programming language (e.g. Python, R) and basics in the area of data structures and algorithms.
- Self-motivation, discipline and the ability for self-organised learning, as distance learning requires a high degree of independence.
- Willingness to actively participate in cooperative online formats and to communicate with lecturers and fellow students.
- Interest in practical applications and the transfer of theory to real data-based problems.
What content and skills does the Master’s programme in Data Science impart?
In the Master’s programme Data Science at FernUniversität Hagen, you acquire solid specialist knowledge in the core areas of computer science, mathematics and statistics. The curriculum is practice-oriented, modularly structured and covers the entire Data Science Life Cycle. The central topics include:
- Data preparation and management – techniques for collecting, correcting and integrating large volumes of data
- Data analysis and data visualisation – exploratory statistics, descriptive analysis, visualisation methods
- Data mining and machine learning – pattern recognition, algorithmic approaches to machine learning, application of AI methods
- Big Data technologies – handling large, complex datasets and relevant software
- Development of data-driven applications – from requirements analysis to implementation
- Mathematical and algorithmic fundamentals – linear algebra, probability theory, optimisation, efficient algorithms
- Use of Data Science-specific programming languages – especially Python or R
- Economic and organisational aspects – role and integration of Data Science in companies, project management
You learn to independently work on a data-based question from initial analysis to solution presentation. The content is based on the recommendations of the Gesellschaft für Informatik for Data Science programmes and is continuously adapted to current developments. Thanks to the broad range of elective subjects, you can set individual focus areas – for example in Artificial Intelligence, Deep Learning or Visual Analytics.
How is the Data Science distance learning programme at FernUni Hagen organised?
The Master’s in Data Science is part-time alongside employment, entirely offered as distance learning and aimed at students with a first degree (particularly in mathematics or computer science). It comprises 120 ECTS and typically lasts four semesters full-time. Alternatively, you can complete the programme part-time and extend the duration individually.
- The start of studies is possible each summer and winter semester (1 April or 1 October).
- The learning materials are provided in writing as study letters (by post and digitally) as well as via an online platform.
- Digital teaching formats such as online lectures, tutorials, virtual seminars and exercise platforms accompany self-study.
- Communication and support are provided through forums, email, regular online consultation hours and mentoring sessions.
- Practical components: project internships and the master’s seminar in Hagen link theory and practice, fostering project management and teamwork.
- Modules are assessed at examination centres throughout Germany, online or occasionally in presence in Hagen. Typical examination formats are exams, term papers and the final master’s thesis on a practice-relevant topic.
- The programme is flexibly planned – you can decide the number of modules per semester yourself and adapt your learning pace to your professional and private situation.
Thanks to modern digital infrastructure and nationwide campus locations, participation is possible regardless of location and time. Support by teaching staff, mentoring sessions and online communities is a priority in order to ensure close contact even in distance learning.
Which career paths are open to you after the Master’s in Data Science?
With the degree Master of Science (M.Sc.) Data Science, you qualify for leading positions in companies, authorities and academia. The demand for data-capable specialists is growing across industries, especially in:
- IT companies – development of Big Data solutions, data engineering, software development
- Healthcare sector – analysis of medical data, bioinformatics, research
- Finance and insurance sector – risk modelling, fraud detection, market analyses
- Transport and energy industries – data-driven process optimisation, forecasting models
Typical job descriptions and professional profiles for graduates are:
- Data Scientist – method development and implementation of complex data projects
- Data Analyst – evaluation of large data sets to support decision-making
- Data Engineer – building and maintaining data infrastructure and pipelines
- Data Manager – data strategy and management within the company
- Data Visualizer – creation of meaningful dashboards and visualisations
A doctorate (PhD) is also possible with the Master’s degree, for example in computer science, mathematics or data science. The programme thus offers a wide range of development opportunities for the path into leadership, expert roles or an academic career.
How much does the Master’s in Data Science cost and what financing options are available?
The costs for the Master’s programme Data Science at FernUniversität Hagen are significantly lower than with private providers and amount to a total of approximately
- €60 basic fee per semester – regardless of individual study progress
- €11 per ECTS – for each credit point taken in the semester
The actual costs vary depending on personal progress (full-time/part-time, number of modules taken). When extending the programme by additional semesters, the total sum increases accordingly by further basic fees (each €60 per semester).
In addition to tuition fees, travel and possibly accommodation costs may be incurred for individual in-person appointments (e.g. seminars, exams). Learning materials and scripts are included in the price, optional specialist literature or working materials may be added.
- FernUni Hagen offers regular fee reductions and tips for study financing, e.g. for those in financial need or for second degrees.
- Study costs can be claimed as tax-deductible work-related expenses.
- Financial support via BaföG is possible in individual cases (according to legal regulations); education loans or funding programmes are also options.
- Employers also regularly financially support the studies, especially when there is strong professional relevance.
Thanks to the affordable fee model, the programme remains affordable even with extended study duration and offers a high return on investment for your academic and professional development.
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