Bachelor's Degree Programme
| About the programme Language: English | Place of study: Aarhus | Commencement: August / September Admissions area number: To be announced after 1 Dec |
Vast quantities of data are being gathered on all aspects of our society. This is what we call 'big data'. Data science is for those who want to explore and understand data. Replacing gut feelings with hard facts.
As a data scientist, you will extract knowledge from data, enabling both society and businesses to make important/critical, evidence-based decisions. Therefore, in addition to learning how to handle and analyse large datasets, you must also be able to communicate your findings effectively.
In the Data Science programme, you will delve into areas such as statistics, data analysis, mathematical modelling, programming, and machine learning.
Data is everywhere, and the knowledge you gain will be in high demand across all sectors of society. You can work with data related to financial markets, the healthcare sector, consumer behaviour, climate change, and much more.
On this page, you can learn more about the structure of the programme, your career opportunities, and student life in the Data Science programme.
All applicants, both for quota 1 and quota 2, must fulfil the following admission requirements for Data Science:
Qualifying entry examination
You must have a qualifying entry examination.
Specific admission requirements
You must fulfil the following specific admission requirements:
B-level is the Danish subject level, not the grade. We assess your subject levels when you apply.
Grade point Average (GPA) requirement of 6.0 in quota 1
You must have a minimum GPA of 6.0 and a minimum GPA of 6.0 in Mathematics A on the Danish 7-point grading scale in your qualifying examination to be assessed in quota 1.
If you do not have a GPA of 6.0 on the Danish 7-point grading scale, then your application can only be assessed in quota 2.
In quota 1, you must fulfil the above-mentioned admission requirements.
Quota 2
In quota 2, you must fulfil the above-mentioned admission requirements except the GPA requirements of 6.0. In quota 2 we assess your application by 2 criteria:
1. Your grade point average of the following particularly relevant quota 2 subjects:
2. Your relevant qualifications
Relevant qualifications
If you can document that you have particularly relevant qualifications, then these can be a part of your overall quota 2 assessment.
Examples: education or work experience in programming, data and software development, IT security, IT support, web development, artificial intelligence.
You can find more information about quota 2 and how to document your relevant qualifications here
Below, you'll find the academic regulations for the Bachelor’s programme in Data Science. In the academic regulations, you can read more about the requirements you must meet as a student and about the programme structure. You can also read about the types of examinations and exam requirements.
The language of instruction for the programme is English.
The diagram below shows how the programme is structured. In the diagram, you can click on the various subjects to read the individual course descriptions.
In the first year of the programme, you will take courses covering fundamental mathematical concepts, including methods in algebra, calculus, statistics, and probability theory. You will also work with basic programming and data management.
In the second year, you will delve into advanced statistics and programming, including statistical modelling, advanced algorithms, optimization methods, and machine learning. Additionally, you will expand your knowledge of databases, data management, and understanding data structures.
The data project, which concludes the second year, will be case-based and train you in the practical application of your acquired knowledge on real-world datasets. This project is done in groups and will involve research groups from various parts of the university, enhancing your skills in collaboration and communication.
In the third year, you have the opportunity to choose electives that can be used to strengthen your knowledge in areas of particular interest to you – such as advanced statistics, bioinformatics, econometrics, or programming. Alternatively, you can expand your understanding of the fields where data science is applied – such as finance, sensor technology, healthcare, or molecular biology. The third year concludes with a bachelor's project focused on solving a real-world problem that requires the application of methods from data science.
The teaching in Data Science typically combines lectures and theoretical exercises with a strong emphasis on case-oriented activities. These case activities are based on real-world issues, and throughout the study programme, there will be continuous interaction with the job market where you will eventually work after graduation.
You should study Data Science because you want to work with methods such as neural networks and machine learning, perfectly blended with mathematics, statistics, and computer science. – Professor Jens Ledet Jensen, Department of Mathematics
You will have approximately 20 teaching hours per week in the Data Science programme, and you should expect to spend a similar amount of time on independent work. This independent work includes preparation, working in study groups, self-study, assignment writing, and, importantly, problem-solving. Later in the programme, the number of scheduled hours decreases as the demands on your independent studies increase.
Part of the teaching hours are dedicated to 'theoretical exercises', often referred to as 'TØ'. In these sessions, small groups of students collaborate with an instructor to work through the weekly assignments. Theoretical exercises are not traditional lectures; instead it is the students' responsibility to review the assignments together, with the instructor — typically a senior student — providing assistance as needed.
The work in the Data Science programme is very diverse. There is as much emphasis on assignments and written submissions as on reading.
Example of a weekly schedule for first-semester students at Data Science [Dette skema skal oversættes/dubleres til engelsk, når der ligger engelske kurser vi kan linke til i kursuskataloget]
The Department of Mathematics is almost always bustling with activity. Many students spend a lot of time at the university, working on assignments together in groups. Many also engage with the programme’s various student organisations, which you can read more about below.
Groupwork
At the start of your studies, you will be assigned to study groups, which you are encouraged to meet with, work on assignments with, and generally collaborate with. For many, hearing other students' perspectives and ideas for solving problems is beneficial. While some may have found group work burdensome in secondary school, it becomes essential and rewarding at university. Your study group can help structure your day, which is much more flexible than in secondary school.
MatLab
Teaching in Data Science combines lectures and smaller group exercises, where you will present, participate in discussions, and solve problems. The academic centre for the programme is the Department of Mathematics, which includes the Mathematics Laboratory. In Data Science, it is crucial to integrate academic and social aspects. You can experience this in the Mathematics Laboratory (MatLab), where you can work on problems while lecturers and senior students are available to help. You are always welcome to ask for help, even if it is not directly related to the exercises. The Mathematics Laboratory is like a structured study café, where there is also room for coffee, cake, or listening to a lecturer discuss academic topics and the programme.
The Department of Mathematics offers many social and academic student societies run by volunteers. These societies host festive traditions and events where you can meet fellow students, including those from other disciplines.
Datavenskab
Although Data Science is a relatively young programme at Aarhus University, students have already established their own student association called Datavenskab (Data Friendship). The association organises both academic and social events across all years of the Data Science programme.
Kalkulerbar (Friday bar)
Every Friday afternoon, you have the opportunity to spend some enjoyable hours at Kalkulerbar, the Friday bar for Mathematics, Mathematical Economics, and Data Science.
Several times each semester, there are quizzes and beer pong evenings.
TÅGEKAMMERET
The party and lecture association is called TÅGEKAMMERET.
Besides organising parties and lectures, the society’s meeting room serves as a social hub for students.
In Aarhus, nearly every 5th resident is a student - making it a city with many young people and offerings tailored to students. When you start your studies in Aarhus, you don't need to worry about being without a roof over your head. There's a housing guarantee for new students moving to the city. The guarantee applies to all newly admitted students to an education in Aarhus starting in the autumn semester. Simply meaning that once you enter the queue, you move up over a few months and are offered a dormitory or youth housing before or shortly after the start of your studies.
- experienced, photographed and filmed by the students themselves.
With thousands of pictures #yourniversity 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 #Yourniversity, #AarhusUni and course-specific AU-hashtags.
Or follow the everyday life at the Department of Mathematics:
As a Bachelor's graduate in Data Science, a natural progression would be to pursue a Master's degree in Data Science. As a Master's graduate, you can find employment in industries where handling large datasets is essential, such as the financial sector, pharmaceutical industry, healthcare, manufacturing companies, business intelligence, and logistics. The demand for such skills is expected to increase significantly due to technological advancements and an increasing demand for solid, evidence-based information. Graduates with a background in data science can hold roles at all organisational levels – from project team member to management.
A Bachelor's degree in Data Science also provides access to a Master's programme in bioinformatics, and with appropriate electives, one can pursue a Master's degree in computer science as well.
A PhD is a research education where you undertake an independent scientific project culminating in an advanced research paper. You can apply for a PhD programme in your field based on your Bachelor's or Master's degree. You apply through a PhD project focused on the topic you will work on and research. You will be assigned one or more supervisors who will assist and guide you throughout your studies. In addition to the PhD project, you will enhance your skills through national and international PhD courses and in active research environments. You will also gain experience in teaching and communication, as well. The degree offers numerous career opportunities both domestically and internationally, within academia and the private sector. You can read more about the conditions and salary on the PhD school's website.
