Applied Data Science Master's Programme
Summary
The programme is not accepting applications for Autumn 2025.
We recommend you instead to consider our master programmes in Computer Science (N2COS) and Software Engineering and Management (N2SOF). The majority of the courses previously given within the paused Applied data science programme will still be available as elective courses as part of these other master programmes.
About
Data science is concerned with extracting meaning from large volumes of data. It is a field that has grown rapidly in recent years as a result of the increasing availability of large data sets and the opportunities and challenges that they present. Central topics within data science include data mining, machine learning, databases, and the application of data science methods in natural sciences, life sciences, business, humanities, and social sciences, as well as in industry and society.
Watch our film about the programme
Training in the management and analysis of large-scale data
Data science is having a big impact on industry. For some companies, being able to handle and analyse massive data sets is central to their business model. Even for other companies, being able to extract information from data (for example, data about customers) can offer crucial competitive advantages. People with knowledge and skills in data science are therefore in high demand, in Gothenburg, in Sweden, and internationally. Similarly, within scientific research, data-intensive scientific discovery is increasingly important in many areas, and researchers need to be able to handle and analyse massive data sets.
Welcoming students with backgrounds in many different areas
The master’s programme in Applied Data Science is designed to be accessible to students with a wide range of bachelor’s degrees, and a master’s education in applied data science will be of benefit to students with backgrounds in many different areas who recognize that being able to work effectively with large data sets will be important in their future careers. Some previous programming experience is required, and the programme builds on this. Some examples of general programming languages that provide a good foundation are Python, Java, C, C++, and C#. Languages such as Matlab, SQL, R, and Prolog do not provide sufficient knowledge.
This master's programme gives students an overview of the techniques and technologies that are relevant to data science, an appreciation of when and how they can be used, and practical skills for their application.
Since we welcome students with various backgrounds you can help us by downloading and filling in the following form, to help us assess the prerequisites for the program. The form also contains room for your motivation letter. Please submit the form together with your transcripts and other documents in the application system.
The reason for starting a master's programme in Data Science
Student interviews
Fionn Delahunty: From Psychology to Applied Data Science
Katalin Ferenc: From Biomedicine to Applied Data Science
Alumni interviews
Sören Stahlschmidt: Went directly into a trainee programme at SKF
Nathalie Gocht: From Applied Data Science to the startup world
Razan Ghzouli: Pursuing a PhD degree in Software Engineering
Programme structure and content
This two-year programme includes the following compulsory courses that provide a core within data science:
- Introduction to Data Science
- Python for Data Scientists
- Applied Mathematical Thinking
- Statistical Methods for Data Science
- Applied Machine Learning
- Computational Techniques for Large-Scale Data
- Research Methods for Data Science
- Master’s Thesis in Data Science
Applied data science is multidisciplinary by nature, and the programme is designed to allow space for you to create your own profile by choosing optional courses. You can choose courses in areas where data science methods can be applied, or courses in technical areas that feature techniques and technologies that complement those introduced in the programme's mandatory courses. You are particularly encouraged to supplement the mandatory courses that provide a core in data science with optional second-cycle courses in the area of your bachelor’s degree.
Who should apply?
The two-year master’s programme in Applied Data Science is an international full-time on-campus programme open to both Swedish and international applicants. The programme is available to students from diverse backgrounds with basic programming skills.
If you have some previous programming experience and recognize that being able to work effectively with large data sets will be important in your future career, then apply to the master’s programme in Applied Data Science.
Prerequisites and selection
Entry requirements
A Bachelor's degree of 180 credits including an independent project (degree project) of at least 15 credits or equivalent.
7\.5 credits from courses in programming in a general-purpose programming language or equivalent, and 7.5 credits mathematics or statistics, no courses on pre-university level.
Applicants must prove their knowledge of English: English 6/English B from Swedish Upper Secondary School or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.
After graduation
Graduates of the programme will receive the degree Master of Science in Applied Data Science.
With this programme you will obtain advanced knowledge in applied data science, and once the programme is completed you will be able to either
pursue a specialist career in industry or move ahead in academic
research.
You will be prepared to work with Big Data in your
future career. You will learn about different data science methods,
their applicability, and advantages and disadvantages of different
techniques. You will have the knowledge and skills necessary to respond
to the challenges and opportunities that emerge as massive data sets
become increasingly available.
Facilities
The master's programme is given by the Department of Computer Science and Engineering, which is shared between University of Gothenburg and Chalmers University of Technology. The department's main campus is Johanneberg.
