MSc Data Science
The English-language master program Data Science provides a scientifically and methodically founded education that is focused on lasting knowledge, enabling you to pursue both academic paths in subsequent doctoral studies and careers in a range of industry and business settings.
- Duration: 4 Semesters
- ECTS Worth: 120
- Degree: Dipl.-Ing. (i.e., MSc)
- Language: English
- Curriculum: PDF / Courses
- Questions? — We have answers
Diese Seite in Deutsch.
What are the contents of the program?
Data Science deals with large, heterogeneous data (big data) from various application areas (e.g. production, energy, environment, health, social sciences) and aims to obtain valuable and meaningful findings and generate actionable information. Tasks in Data Science include obtaining a thorough understanding of the problem domain (Business Understanding), processing and fusion of heterogeneous data from different sources (Data Gathering), analysis and statistical modeling of the Data (Data Analytics), as well as interactive visualization of the data (Visual Analytics) and the use of the results (Decision Support and Deployment).
Furthermore, requirements in terms of reproducibility of results and reuse of data (Data Curation) and the deployment within large data centers are of central importance. This program conveys and integrates competences from the fields of information technology and mathematics as well as specific application disciplines—qualifications which are increasingly demanded in science and business.
The curriculum builds upon a few central foundational subjects which are extended by selecting at least three of the following four Key Areas: Fundamentals of Data Science, Machine Learning and Statistics, Visual Analytics and Semantic Technologies, Big Data and High Performance Computing. Each key area consists of a mandatory “gatekeeper” module (core module) and an extension module, from which you can individually select thematically relevant courses.
Which qualifications do I acquire?
You receive extensive knowledge in a variety of topics such as mathematical foundations and methods of data science (in particular statistical data analysis and modeling), concepts and methods in specific informatics aspects of data science, in particular data infrastructures, data management, data analysis and visualization. You acquire solid basics and methods in selected areas of other scientific disciplines (such as architecture, astronomy, biology, chemistry, digital humanities, earth sciences, medicine, physics, social sciences).
Your cognitive skills are further developed and let you scientifically analyze systems, obtain an integrative view, and select the most suitable methods for modeling and abstraction. Your work methodology is goal-oriented, and you will be able to present results convincingly in an interdisciplinary environment.
Social skills such as self-organization, personal responsibility, communication, and the reflection of your own abilities and limits are strengthened. You will be able to assess the impact of your results and to evaluate them on an ethical basis.
What can I do with my degree?
As a graduate, you have obtained an in-depth, scientifically and methodically founded education that is focused on lasting knowledge, enabling you to pursue both academic paths in subsequent doctoral studies and careers in a range of industry and business settings.
You are qualified to act as a link between the technical infrastructures and the domains in research and development in industries such as pharmaceutics, operations research, nanotechnology, marketing, logistics. You are capable of deriving and understanding complex interrelationships, patterns and knowledge from raw data in a structured manner and to communicate the results.
You have the competencies to setup and operate data and computing centers, and are able to support research and innovation in the field of Science both from a core technical and an interdisciplinary perspective to drive the development of data-driven technologies.
You are deeply immersed in a rich environment full of exciting ideas and interesting challenges that foster your talents and provide new experiences:
- Participate in our student mobility programs! International exchange is in our DNA. Meet students, researchers, and lecturers from all over the world, participate in Erasmus, and join our double degree programs during your Masters.
- Come for the Master; stay for the Doctorate! A master’s degree is the ideal preparation for a doctorate at the TU Wien Informatics Doctoral School. And we are always looking for excellent candidates for open positions in the scientific field.
- Get to know the people and research! We are proud of the distinguished scholars and researchers who make up our diverse faculty. Find out who they are, what projects our research units are working on, and stay in touch through our newsroom and social media channels.
- Enjoy Vienna! Our campus is located directly in the heart of Vienna. Besides Vienna ranking as the city with the highest quality of life and TU Wien Informatics in the Global Top 15% in Computer Science, there are numerous more reasons why you should study with us.
You’re more than just a number when you study with us. Be part of TU Wien Informatics!
Frequently Asked Questions
What are the requirements regarding German and English?
For German, none. The program is entirely in English. If an application form asks for your German skills, this is only because of other study programs; your answer does not affect the chances of getting admitted.
For English, proficiency on Level B2 of the Common European Framework of Reference for Languages.
How do I apply?
How is my application evaluated?
Your application is processed in three steps:
The admission office checks whether your application meets certain formal requirements. You need a degree on level 6 (bachelor) or higher in the European Qualifications Framework, and it should have been awarded by a recognized institution (classified as “H+” in ANABIN ). Depending on your country of origin, further conditions may apply.
We check whether your bachelor degree covers fundamental education in the area of computer science, mathematics, and statistics.
We check whether the documents you have supplied with the application (like degrees, transcripts, certificates) allow us to conclude that your expertise in computer science, economics, business informatics, and mathematics suffices to follow the master courses successfully.
At the moment, there is no restriction on the number of students admitted per term. You don’t have to compete against other applicants for a limited number of places.
Will I be admitted with or without conditions?
If you have completed your bachelor degree in Business Informatics at TU Wien you will be admitted without further conditions. If you have completed one of the bachelor programs in Informatics at TU Wien you will be admitted, but you will have to do extra courses on economics.
Otherwise we check, based on the documents that you have provided with your application, whether you have the necessary prerequisites for mastering the courses in the programme. If you have, you will be admitted without further conditions. If not, we compile a list of missing prerequisites. If they sum up to a term (half a year) or less, you will be admitted under the condition that you do some extra courses. You don’t have to do them in advance, but can do them side-by-side with the regular master programme, as we check their completion only at the end of your studies here.
If the missing prerequisites exceed a full term, we have to reject your application.
What are the admission requirements?
We check your documents (like transcripts and certificates) for expertise in the following four areas: algorithms and data structures, programming, database systems, mathematics, and statistics; for details see the modules INT/ADA (8 ECTS), INT/PRO (9.5 ECTS), WIN/DBS (6 ECTS), STW/MAT (15 ECTS), and STW/STA (6 ECTS) of the bachelor programme in Business Informatics at TU Wien.
The numbers in parentheses indicate the extent of the area, measured in credits according to the European Credit Transfer System. One Ects corresponds to 25 hours of student work, 60 ECTS correspond to the work load of a year.
We are not picky about single ECTS credits, but you need a solid foundation in these areas to be admitted without further conditions. If you lack some of these foundations (up to 30 ECTS), you can be admitted under the condition that you do some extra courses to make up for it.