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Deutsch Who is the Master’s in Data Science & Analytics suitable for?
The Master’s programme in Data Science & Analytics is aimed at professionals who already have a degree in computer science or a natural science and possess practical experience in handling data. It is particularly targeted at specialists from IT, business informatics, engineering sciences, mathematics and related disciplines who want to design data-driven decision-making processes in companies and apply artificial intelligence as well as data analytical methods. The programme is ideal for individuals who wish to work as Data Scientists, Data Analysts, (Big) Data Engineers or in the fields of Machine Learning and Business Analytics.
What formal admission requirements do you need to meet?
Different requirements apply depending on the chosen ECTS variant:
- 60 ECTS variant (standard study period 2 semesters):
- Completed university degree in computer science or natural sciences (at least Bachelor’s)
- At least 2 years of relevant professional experience after the first degree
- English language skills at level B1
- Proof of basic digital-scientific understanding
- Participation in an aptitude test or alternatively a motivation interview with the programme director
- 90 ECTS variant (standard study period 3 semesters):
- Completed (university of applied sciences) degree (at least Bachelor’s)
- At least 1 year of relevant professional experience after the first degree
- English language skills at level B1
- Basic digital-scientific understanding
- Motivation interview with the programme director
- 120 ECTS variant (standard study period 4 semesters):
- Completed (university of applied sciences) degree (at least Bachelor’s)
- At least 1 year of relevant professional experience after the first degree
- English language skills at level B1
If you do not have a directly relevant first degree, you must demonstrate your basic digital and scientific aptitude in an individual selection procedure.
Important are a interest in working with large data sets and willingness to work on data-based questions in a structured and systematic way. Practical experience in analysing and preparing data, mathematical-analytical thinking as well as knowledge of statistics, programming or business intelligence are helpful. You should be able to work independently, have perseverance in solving complex problems and be open to new digital technologies and interdisciplinary contexts. The ability to communicate analytical results clearly and to reflect on ethical and data protection aspects is essential in the later professional field.
What content is taught in the Master Data Science & Analytics?
In the Master’s programme Data Science & Analytics at SRH Fernhochschule, you acquire comprehensive skills in the key areas of data analysis and artificial intelligence. The curriculum combines statistical methods, programming and business management thinking to support data-based decision-making processes in companies. The central topics include:
- Empirical Social Research: Methods of data collection, hypothesis formation and experimental designs
- Data Analysis & Data Management: Preparation, evaluation and quality assessment of large data volumes
- Artificial Intelligence & Machine Learning: Construction and training of models for pattern recognition and prediction
- Big Data Management & Analytics: Organisation, analysis and interpretation of extensive, heterogeneous data sets
- Requirements Analysis and Communication: Goal definition, stakeholder analysis and clear presentation of complex analysis results
- Statistics and Machine Learning Models: Application of classical and modern statistical methods in a business context
- Data Protection, Ethics and Law: Handling legal and ethical issues in the data lifecycle
- Specialisations: Optional specialisation in Machine Learning or Business Analytics for individual profile development
A central element is the practical project, in which you apply acquired knowledge to real data and business scenarios. In addition, you develop skills in team leadership, planning data strategies and implementing sustainable data projects while considering ethical standards.
How is the Master Data Science & Analytics organised?
The programme is offered exclusively as a distance learning course and is specially tailored to the needs of working professionals. Learning independent of location and time is the focus: You work on study materials, participate in digital events and maintain direct contact with lecturers and fellow students via the online campus.
- Duration: 2 semesters for the 60-ECTS variant, alternatively 90 or 120 ECTS with a longer duration selectable
- Individual time planning: Monthly start possible, flexible module completion, free extension options
- Learning format: Mobile learning via digital platforms, self-study, digital live events (mostly optional)
- On-site sessions: Exams and optional events can take place at 22 examination centres in Germany, Austria and Switzerland
- Final thesis: Master’s thesis in the last semester with a research or practice-oriented focus
During the course of study, you choose one of two specialisation directions: Machine Learning (focus on AI methods and model development) or Business Analytics (data-driven corporate management). The study concept promotes self-organised and practice-integrated work.
For which professions does the Data Science & Analytics degree qualify you?
With the Master of Science Data Science & Analytics, you are qualified for key roles in the data-driven job market. Typical fields of activity after graduation:
- Data Scientist: Development, training and evaluation of AI and analysis models for companies
- Data Analyst: Structuring, visualisation and interpretation of company data to support decision-making
- Machine Learning Engineer: Implementation and optimisation of algorithms for automated systems
- Big Data Engineer: Construction and management of big data infrastructures and data pipelines
- Consultant Data Analysis & Reporting: Consulting on the introduction of data strategies and business intelligence solutions
- IT Consultant Artificial Intelligence: Development of solutions in the field of applied AI
- Innovation Manager Data Science: Managing data-based change processes in companies
According to current market analyses, average salaries for Data Scientists are around €66,900 gross per year. Specialists with solid technological, statistical and communication skills are particularly in demand. The competencies acquired during the course open career paths in industry, research, consulting and public administration.
Where does the distance learning programme Data Science & Analytics take place?
The distance learning programme at SRH Fernhochschule – The Mobile University is designed to be location-independent. You learn and work via a modern online campus from any location you choose.
- Central university address: Kirchstraße 26, 88499 Riedlingen (Baden-Württemberg)
- Examination centres & optional on-site phases: At currently 22 locations in Germany, Austria and Switzerland, exam and event venues are available for optional meetings and exams.
- Support & supervision: Personal advice and supervision take place digitally and by phone on request.
The online studies offer maximum flexibility: You are not bound to fixed lecture times or to a specific study location. Exams and voluntary on-site events can be taken at a location of your choice.
What tuition fees and financing options should you expect?
The tuition fees for the 60-ECTS variant of the Master Data Science & Analytics amount to a total of €8,588, spread over 2 semesters with a monthly rate of €509.
- Alternative pricing models: The university offers flexible models for longer payment periods (e.g. 16 months x €616.50 monthly; total €9,864). Promotional discounts such as the “Ready Bonus” with up to €1,000 price advantage are possible.
- Variable study durations: You can choose between models with different durations and monthly fees (e.g. 90 or 120 ECTS version with correspondingly adjusted costs).
- Included services: All digital learning materials, access to the online campus and individual support are included in the total price.
- Funding options: Possible financing through tax deductibility, scholarships and government funding programmes. Part-time studies can be supported by employer contributions.
For examining financing solutions, it is advisable to use individual options – for example instalment plans, scholarships or support from your employer.
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