Master's Degree Programme
| About the programme Language: English (See language requirements) | Place of study: Aarhus | Commencement: August / September and January / February (only applicants with a Danish Bachelor's degree) |
The Master’s degree programme in Data Science focuses on both general and specialist competences. You will acquire general competencies through three compulsory courses covering advanced statistical learning, large scale optimization and data visualisation. You will develop specialist competences through a 30 ECTS specialisation package, and you can choose between the following four packages: Computational Statistics, Data-Intensive Systems, Finance and FinTech and Signal Processing.
The programme is taught in English, and large parts of it can be designed to match your specific academic interests, through elective elements and through your choice of specialisation package.
A degree in Data Science will offer job opportunities in many different companies and organisations. The common denominator is the need to create data-driven solutions in these companies and organisations, for example in the wind turbine industry, consultancy firms, pharmaceutical companies, the telecommunications industry, the food industry, the healthcare sector etc. You may also choose to continue your studies on the PhD degree programme, and pursue a career in research.
The following Bachelor’s degree programmes qualify students for admission to the Master’s degree programme in data science:
Other Bachelor’s degree programmes may qualify students for admission to the Master’s degree programme in data science if they meet the following requirements:
Further requirements for the composition of the study programme may be made in connection with admission.
Download appendix for your application
If you apply for admission with an international Bachelor's degree, you must fill in this appendix and upload it in the application portal. The appendix serves to help the Admission Board assess your Bachelor’s degree in regard to the admission requirements.
Language requirements
As the language of instruction is English, all applicants without a legal right of admission must document English qualifications equivalent to Danish secondary school B level from a Danish upper secondary school.
Legal right of admission
Students of the Bachelor’s degree programme in data science at Aarhus University have a legal right of admission to the Master’s degree programme in data science, on the condition that the candidate applies for admission to begin the Master’s degree programme within three years of completing the Bachelor’s degree programme. This legal right of admission only applies if the application is received by Aarhus University within the time frame stated above. Read more about legal right of admission.
As this Master’s degree programme only admits a limited number of students each year, meeting the admission requirements does not in itself guarantee admission to the programme.
When evaluating qualified applicants, the admissions committee assesses each applicant on the basis of the following criteria:
Academic background
* Relevant courses include courses with subject areas within mathematics (including linear algebra), probability theory and statistics, programming and databases, optimisation, machine learning and deep learning.
Please note that any grades earned after the application date will be not be included in the assessment of your application.
The selection committee assesses applications based on the enclosed exam certificates, grade transcripts and course descriptions.
The two-year Master’s degree programme consists of three compulsory courses:
• Advanced Statistical Learning 10 ECTS
• Large Scale Optimization 10 ECTS
• Data Visualization 10 ECTS.
In addition, the programme includes a 30 ECTS specialisation package, where you can choose between:
• Computational Statistics (30 ECTS)
• Data-Intensive Systems (30 ECTS)
• Finance and FinTech (30 ECTS)
• Signal Processing (30 ECTS).
Furthermore, the programme includes elective course elements totalling 30 ECTS and a Master's thesis of 30 ECTS.
Your individualised study programme will be designed on the basis of your interests and with guidance from the head of degree programme for the Master's in Data Science.
A description of the four specialisation packages as well as the elective courses is available on the study portal: Valgfrie kurser for Datavidenskab (in Danish)
As a student it is important to know the regulations for your the chosen subject: what is the content, how is it structured and what does it require from you. You can find this information in the academic regulations
The programme has been approved with English as the language of instruction. The language of instruction is the language in which the programme is generally taught.
The Master's degree programme in Data Science is organised in two semesters per academic year. Below, you can see the structure of the degree programme.
The Master's degree programme in Data Science is based at the Department of Mathematics, as well as three other departments (Computer Science, Economics and Business Economics and Electrical and Computer Engineering), depending on your choice of specialisation package and other elective elements. Teaching is by active researchers and includes both theoretical and practical elements.
Data Science has its own student organisation, and there are also other student organisations at the Department of Mathematics, for example Kalkulebar, the department’s Friday bar, which organises academic and social activities, study trips and parties. You will also meet Tågekammeret, a committee that arranges parties and talks at the Faculty of Natural Sciences at Aarhus University.
-experienced, photographed and filmed by the students themselves.
With thousands of pictures #AUInternational, #AarhusUni gives insight into the everyday life as a student at AU; the parties, procrastination, exams and all the other ways you’ll spend your time at university.
The photos belong to the users, shared with #AUInternational and #AarhusUni.
