Data Science
At a glance
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, extension to 5 semesters possible
Place of study
Language of instruction
German and English
Start of studies
Winter semester (October 01);
Summer semester (March 15)
Admission requirements
- University degree or other equivalent degree with at least 14 ECTS in mathematics/statistics and 14 ECTS in computer science
- Generally 210 ECTS including a practical semester; for degrees with 180 ECTS, missing ECTS in theory or practice can be made up before the start of studies or within one year after the start of studies. Recognition is possible.
- German and English language level B2
- You can find more information in the study and examination regulations
- For international applicants: all information about the application including an overview of the required language certificates here
Costs
Semester fee (incl. semester ticket)
Semester abroad
Possible as a theoretical or practical semester
Studying with a practice partner
On request as a degree course with in-depth practical experience (PraxisPlus)
Accreditation
is accredited
Registration
from May 2 – September 30 (for the winter semester)
from November 15 – March 14 (for the summer semester)
Profile of the Master's program
Career rethought: If you are interested in data, AI and smart solutions, even if you have previously worked in a different field, data science is your turbo upgrade. Entry desired – lateral entry expressly welcome.
The Master's degree program in Data Science is aimed at graduates from various disciplines – from engineering, natural sciences and economics to computer science – who want to expand their specialist knowledge specifically for the digital future. You will combine your existing know-how with modern methods of data analysis, artificial intelligence, statistics and software development.
The focus is on gaining useful knowledge from data: Recognizing patterns, developing models, understanding correlations and making well-founded decisions. It is precisely these skills that are in demand in a working world in which products, processes and business models are increasingly data-driven.
The degree program prepares you for challenging tasks in companies, for management roles in data-intensive areas and for activities in research and development. You will also learn how to communicate results clearly and use data responsibly.
What we value
Learning what really counts
With us, you will work on real data science problems – from Industry 4.0 and sustainability to AI applications in regional companies. You will experience how data changes real decisions.
Hands-on instead of just slides
You don't just sit in lecture halls – you develop models, train algorithms, visualize data and build functioning prototypes. Whether Python, machine learning or cloud tools: You work with technologies that are actually used outside.
Your head, your ideas
Data science thrives on curiosity and creativity. We give you the space to find your own solutions, test hypotheses and design data-based innovations. No rigid learning plan, but freedom for real explorers.
Focus on people
AI and data are powerful – but responsibility, teamwork and communication are crucial to their success. That's why we not only strengthen your technical skills, but also your ability to lead projects, communicate results and shape change.
Modern exams that suit you
Yes, there are still exams – but not only! We also include development projects, data-based case studies, teamwork, presentations and computer-based exams. We don't just test knowledge, but real data skills.
Gain international experience
Want to see the world? Then take your chance!
As a student at Coburg University of Applied Sciences, you have the opportunity to complete a study or internship semester abroad – whether in Europe, the USA or Asia. The university works with numerous partner universities and supports you in choosing a suitable destination.
You can find all the information, tips and contacts in the service area "Studying abroad " – your gateway to the world.
Course content and schedule
Your studies, your content
The Master's in Data Science is not a mass study program, but rather small groups, personal support and students with very different backgrounds. Perfect for learning from each other and growing together.
What you can expect:
- Personal mentoring right from the start
In the Interdisciplinary Perspectives & Study Planning module, you will find out where you stand, what you can do and where you want to go. Your studies will be as individual as you are. - 1. & 2nd semester: Your skill-building phase
Scientific modules, programming, data analytics, AI, big data, visualization, psychology & ethics – plus real projects that put you into practice. - 3rd semester: Your masterpiece
The Master's thesis. This is where you bring together everything you have learned – in research, a company or an individual project.
You start in a structured way, build up skills, work practically – and finish with something that really counts.
Technical basics of IT
What you learn:
- Program like a data scientist:
Python from the basics to real ML workflows – including NumPy, Pandas, TensorFlow & PyTorch. You will learn how to wrangle data, build models and structure code cleanly. - Tools that professionals use:
Git, GitLab, Linux, Jupyter – everything you need for collaborative software development and practical data science. - Understanding & managing data:
From regular expressions to SQL, XML & graph databases to data lifecycle, data quality and architecture decisions. You will learn the toolbox that all data-driven companies use. - Databases in action:
Modeling, querying and optimizing data. Whether relational systems or NoSQL: you develop a feeling for which technology fits which problem. - Big data hands-on:
Apache Spark, distributed systems, cloud concepts and modern architectures for huge amounts of data. You will recognize potentials, limits – and how to use big data efficiently. - Understanding cloud computing:
What does scalability mean? Which architecture makes sense when? And when is the cloud the best solution? You work on real examples and make well-founded decisions instead of repeating buzzwords.
What makes this degree program special:
You don't just learn about IT – you apply it. During your studies, you will program, work with real data sets, develop data pipelines, evaluate architectures and make well-founded technical decisions.
The modules teach you step by step the basics that are crucial for a successful career in data science: professional software development, reliable data infrastructures and modern cloud architectures.
Data analysis & AI
What's waiting for you:
- Math that really makes a difference:
Linear algebra, statistics, multivariate methods, machine learning basics. You will learn exactly the mathematical skills that drive modern AI – without unnecessary ballast. - Data mining – recognize patterns, make decisions:
Clustering, classification, anomaly detection, association analyses. Find structures in data that remain hidden to others – and evaluate them critically. - Deep learning – building models that learn themselves:
Neural networks, CNNs, RNNs, autoencoders, LSTMs. You will work with TensorFlow and PyTorch and make AI work on real data sets. - Data Visualization – letting data speak for itself:
You transform complex information into clear, effective visualizations. Whether interactive dashboards, multidimensional data or visual storytelling. - End-to-end data science:
From the hypothesis to the model to the interpretation – you will learn how to set up complete analysis processes in a structured and methodical manner.
Why that makes all the difference:
Because you learn what AI can really do – and what it can't.
You develop the skills to not only train models, but also to understand, explain and use them responsibly.
Because math, code & creativity come together here.
You will become a professional who can read data, recognize patterns and communicate AI in an understandable way – a real translator between algorithms and decision-makers.
Because companies are looking for just such people.
Data analysis is not just the future – it is the basis for smart decisions in business, science, industry and society.
Scientific methodology
What's waiting for you:
- Scientific work – next level:
You will learn how to formulate research questions clearly, evaluate literature in a structured way and use scientific methods in a targeted manner. - Seminar skills that count:
In-depth study of a specialist topic, critical discussion, written elaboration and presentation. You train the core skills that underpin any good data scientist's career. - Master's colloquium – your research springboard:
You present your Master's thesis like a professional, learn scientific argumentation and develop the ability to write and review specialist articles yourself. - Exchange at eye level:
Giving feedback, accepting feedback, comparing perspectives – science thrives on discourse, and that's exactly what you practise here.
What you get out of it:
Scientific methodology makes you reflective, precise and credible.
You will become a person who not only analyzes data, but also understands the background, argues clearly and communicates results convincingly – in research, in companies and wherever quality counts.
Personality development
What you take with you:
- Mentoring & self-reflection:
In the Interdisciplinary Perspectives module, you will find out where you stand, where you want to go – and how you can develop your skills in a targeted manner. Individual coaching included. - Ethical AI Skills:
In Ethics of AI, you will recognize the opportunities, risks and dilemmas of modern AI. You will learn to make responsible decisions – instead of blindly celebrating technology. - Digital Thinking:
In Digital Transformation, you will develop a growth mindset and understand how companies change, how new business models emerge and how you can actively shape change. - Data protection that really works:
In Privacy & Data Protection, you will learn how to not only know the legal requirements, but also how to implement them in everyday life – with a view to human dignity, responsibility and social impact. - Psychological tools of the trade:
The psychology module shows you how people think, decide, work and communicate. You will learn about leadership, motivation, team dynamics – and how to develop yourself.
Why you need it:
Because data science is more than just math and algorithms.
The difference between good analysis and real impact lies in your personality: in your values, your thinking, your attitude.
Because the best data scientists are communicative, reflective and responsible.
You will become a person who can explain AI, represent decisions, lead teams and deal with complex ethical issues.
Because the future is interdisciplinary.
Technology, society, law, psychology – everything is connected. And you learn to navigate this field of tension with confidence.
In short:
You develop not just skills, but character. And that's exactly what makes you indispensable in your studies, career and society.
Practical semester - the upgrade if you still lack experience
Did you only study for six semesters in your Bachelor's degree and didn't complete an internship semester – or didn't gain any work experience afterwards?
Then you can make up for this practical experience in the Master's program.
In the first year of your studies, you will complete an internship semester in which you will gain insights into a company, work on real projects and gain valuable professional experience. In this way, you combine theoretical knowledge with practical application and strengthen your career prospects at the same time.
You will receive comprehensive support and guidance during your internship semester – so that you gain the practical experience that is important for your future career.
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 course will be answered by the course director Prof. Dr. Thomas Wieland
Insights
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More InformationJob & Career
Specialist staff – why you are in demand now
With data science, you are one of the specialists that companies are currently urgently looking for. This is because almost all industries are data-driven – from automotive and medical technology to gaming and digital platforms.
Understanding data. Enable decisions.
You will learn how to analyze and structure large amounts of data and translate it into well-founded decisions. It is precisely this ability that makes data scientists key people in companies.
Wide range of applications
Whether start-up, medium-sized company or international corporation – data science is in demand everywhere. You can work flexibly: remotely, hybrid or on-site, nationally or internationally.
Broad skills profile
Your studies will provide you with a versatile skillset:
Analysis, modelling, programming, visualization and comprehensible communication of results. This means you are just as much in demand in interdisciplinary teams as in specialized roles.
Career paths
Possible fields of activity include:
Data Scientist, Machine Learning Engineer, Analytics Consultant, Researcher, Product Owner or roles in the field of AI and data strategy.
Practical experience right from the start
Through practical projects, guest lectures, collaborations with companies and your Master's thesis, you will establish contacts with professional practice at an early stage – and gain relevant experience during your studies.
Conclusion
Data Science opens up a wide range of career prospects in a dynamic, future-proof environment. We are looking for people who think analytically, remain curious and want to understand complex relationships.
Do your doctorate now!
After successfully completing your Master's degree, you can further deepen your knowledge with a doctorate at Coburg University of Applied Sciences.
