Data Science
Master's degree
Become an expert in organizing and using large amounts of data. A Master's education in data science gives you a deep dive into the storage and analysis of Big Data in a practical perspective.
Semester start
Admission requirements
To apply for this programme you must have one of these:
- a bachelor’s degree in Computer Science, Computer Engineering or Informatics / Information Technology
- a bachelor’s degree in Physics, Statistics, Mathematics or Applied Mathematics with at least 10 ECTS in programming
- a bachelor’s degree in other engineering subjects with at least 10 ECTS in Mathematics, 10 ECTS in Statistics and 10 ECTS in programming
You must also have:
- an average grade of at least C (according to the ECTS grading scale) on your bachelor's degree
- proof of your English proficiency
Applicants will be ranked on the basis of grade average from their bachelor's degree.
How to apply
You apply via Søknadsweb, where you fill in your details and upload all the required documents.
There are different application deadlines based on which country you apply from:
- 1 November: Admission for international applicants from countries outside of the European Union / the European Economic Area (EEA) / Switzerland
- 1 March: early admission for applicants from the European Union, the European Economic Area (EEA) and Switzerland, and for non-EU/EEA citizens with a Norwegian national ID number residing in Norway
- 15 April: ordinary admission for applicants from the European Union, the European Economic Area (EEA) and Switzerland, and for non-EU/EEA citizens with a Norwegian national ID number residing in Norway
Programme cost
For students from the EU/EEA/EFTA the only cost of this programme is the semester fee (student.oslomet.no) of approximately NOK 1,000, which you pay each semester of the programme. For these students there are no tuition fees.
Programme content
In computer science, you will find elements of Big Data, statistics and machine learning.
With the enormous amount of data from all kinds of electronic devices and systems, the challenge remains to extract knowledge and wisdom from it.
Examples of current challenges where data analysis is necessary are self-driving vehicles that share information and learn from each other, climate data from around the globe, financial transactions from millions of bank customers or genomic data sets from gene banks.
As technology continues to spread into every nook of our lives, new data is generated about us. While valuable insights can be found, the need to protect the data and understand the ethical implications of its use becomes increasingly important.
Being an expert in Data Science involves having practical skills in setting up and using advanced Big Data databases. It then requires expertise in statistics to know which analysis methods are most applicable. Finally, it requires the ability to automate the analysis to turn it into a tool that can be used by others on future, similar datasets.
As a computer science student, you will
- learn to use statistical methods on large datasets in practice
- get practical experience with "state-of-the-art" BigData systems
- get theoretical background in the algorithms and techniques used in computer science
You will have the opportunity to program your own analysis tools based on the methods you have learned on large datasets.
How the programme is taught
You write a master's thesis of either 30 or 60 credits, where you get time to immerse yourself in ongoing research at OsloMet, or work on a concrete and limited project of your own choosing.
All courses are taught in English.
The programme focuses on active forms of learning where you learn advanced theory through the practical use of technology.
You will be expected to take responsibility in your studies, because a completed master's degree must be proof of a good ability to work independently. Therefore, the study's teaching is more closely organized at the beginning than towards the end, where the choices and responsibility rest to a greater extent on you as a student.
You will have a variety of
- lectures
- seminars
- digital learning tools
- group work
- individual work
- lab work
Programme structure
This overview shows all the specialisations in the Master's Degree Programme (MSc) in Applied computer and Information Technology. The subjects in Data Science are listed per academic year under the heading "Data Science".
This overview is updated each spring, and until then it shows the courses available to current students.
This overview is updated every spring; until then it shows the courses for current students.
Year 1
Fall 2026
Exchange
You can go on exchange in the third semester.
Career
The specialisation in Data Science produces qualified senior professionals for both public and private sector, for example consulting engineers, and professionals in innovation and development.
It is not uncommon to get positions such as manager, team leader, subject manager or project manager after a few years of working experience.
As a technologist, you are not tied to a particular sector or industry. Technologists work in health, education, entertainment, public transport and almost every other conceivable part of society .
An advantage of studying technology is that you don't have to decide which sector you want to work in from the start. You can change paths during your career.
The degree also qualifies for PhD programmes, depending on your specialization and grades.
