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Computer Science

Master of Science

The Master's degree programme in Computer science takes two years to complete, and each academic year is divided into two semesters.

The diagramme below gives you an overview of the course of study. On mobile devices it works best in landscape mode.

Specialisations

Each specialisation consists of a number of elective courses and projects, which we recommend you choose from if you wish to specialise in the relevant research area.

  • Algorithms are at the core of computer science and the recent popularity of the word "algorithms" is well deserved. In fact, what is often referred to as "intelligence" in systems is really huge amounts of data combined with advanced algorithms for searching and computing based on these data.

    Algorithms is a focus area at SDU, with an unusually large and strong research group and a large variety of courses in the area.

    In addition to offering expertise in concrete application areas, a solid background in algorithms makes it easy to enter other subareas of computer science. In a fast-moving field such as computer science, the ability to adapt to ever-changing circumstances is important for a successful career.

    All the courses that we offer within this area require knowledge of algorithms and data structures, as well as basic discrete mathematics. Some courses may have further entry requirements and/or academic preconditions. Additionally, please note that some of the courses are not offered every year.

    Recommended courses in Autumn 2023

    Recommended courses in Spring 2024

    Examples of previous thesis project titles

    • European football placement problems - complexities and exact solutions
    • On-line graph colouring
    • Aircraft routing
    • Lattice-based cryptography
    • Nearest neighbour search in high-dimensional spaces
    • Theoretical aspects of computer-aided chemical synthesis design

  • Modern digital systems are no longer single machines operating on their own, but rather complex entities consisting of many different agents working semi-independently and interacting with each other.

    This specialisation focuses on understanding, working with, and programming such complex and distributed systems (Cloud Computing). It combines different expertise ranging from cryptography to logic and programming languages to make the study of systems precise and safe (Cybersecurity). It also explores the usage of industrial tools that fully automate system deployment in efficient and safe ways.

    Cybersecurity and Cloud Computing is a dynamic and growing research field at SDU, in which researchers are excited about taming the complexity of big, highly interacting and distributed systems. We approach the research problems in our area from different angles, ranging from the more theoretical to the more applied perspectives, and have strong ties to industry.

    Please note that some of the courses may not be offered every year,

    Recommended courses in autumn 2023

    Recommended courses in spring 2024

    Examples of previous thesis project titles

    • Foundational aspects of choreographic programming
    • A formal programming model for Bitcoin transactions
    • Packaging microservices

  • The specialisation in Data Science and Artificial Intelligence includes fields such as machine learning, data mining, deep learning, artificial intelligence, optimisation, visualisation, and statistics, and it relates to terms such as data analytics and big data.

    In many areas, incorporating insights from data analysis makes a major difference. Examples of data science in action in our everyday life are product recommendations in online stores or personal assistant systems on smartphones. Many companies want to use data science techniques to optimise their businesses. In the industry, machine learning, optimisation and artificial intelligence are applied in hot developing technologies such as robotics, drones, and self-driving cars.

    In the Data Science group at SDU, statisticians and computer scientists work together for teaching, so we provide expertise in various aspects of our educational programmes as well as a coherent picture. Through close cooperation with other faculties, we are also able to offer courses that connect to the upcoming field of Personalised Medicine, a field which is relevant to everyone and which relies heavily on Data Science.

    We are engaged in data science projects with various companies, from small and medium-sized local companies to big players, which is why we can offer hands-on experience in student projects as well as theoretical research at the forefront of this field.

    For example, we are working with the City of Odense and the municipalities of Kolding, Nyborg and Svendborg on improving traffic systems, the planning of public transportation and the allocation of posts for building maintenance in the yearly budgets. In the industrial sector, we have current and past projects on data analysis and optimisation with companies such as Danfoss, Ørsted, Energinet, Lego, and Aviation Cloud.

    Most of the courses that we offer within Data Science and AI require basic understanding of linear algebra. Please note that some of the courses may not be offered every year.

    Recommended autumn courses

    Recommended spring courses

    Examples of previous thesis project titles

    • Optimisation of demand-responsive personal transportation
    • Synchronisation, Enrichment and Visualisation of Football Data
    • Bus Line Optimisation on Funen
    • Simulation of Traffic Flow in a Real Urban Network
    • Flight Planning in Free Route Airspaces
    • Artificial Intelligence in Action Real-Time Strategy Games
    • Optimising Heat and Power Production Using Column Generation
    • Visual Analytics of Sentiments in Twitter Data

The specialisations should be considered as suggestions to give you a better overview of the elective courses that we offer, but you will not be required to stick to courses from just one specialisation.

Example of a timetable

Below is an example of what a weekly timetable might look like for first-semester students on the Master's degree programme in Computer science. There are, of course, breaks throughout the day, for example the academic quarter. Please note that the timetable varies from week to week and that teaching activities may be scheduled on weekdays in the hours between 8.15 and 18.00.

Monday
Tuesday
Wednesday
Thursday
Friday
8-10
Deep Learning (lecture)
8-10
Visualisation (lecture)
8-10
Visualisation (practice session)




Kl. 10-12
Heuristics and constraint programming for discrete optimization (practice session)



12-14
Heuristics and constraint programming for discrete optimization (lecture)


14-16
Heuristics and constraint programming for discrete optimization (lecture)

16-18
Visualisation (lecture)
  
16-18
Deep Learning (practice session)

The rules for the Master's degree programme in Computer science are specified in the programme regulations, which are the formal description of the programme.

The programme regulations contain information about the purpose and structure of the programme, including which subject elements the programme contains, whether there are opportunities for a semester abroad, company projects, rules for conducting teaching and exams, rules for participation in exams, etc.

See the programme regulations on MySDU

A course description is a detailed description of a course, in which you can read about the aim and contents of the course, teaching methods, the expected workload and the form of the exam.

The Master's degree programme in Computer Science includes the opportunity to complete a company project during the 2nd semester.

A company project is a well-defined project, which is done part-time or full-time in a company or organisation, and which has a scope of 10, 15 or 30 ECTS. A company project places demands on learning on a par with other courses at the university. There is both an SDU supervisor and a company supervisor associated with the project.

The study board must approve the project description before you can start working on the project.

Company projects are always unpaid.

As part of the Master's degree programme in Computer Science, you have the opportunity study abroad at a university outside Denmark, either during the 2nd semester or as part of your thesis project.

You can choose either a university that SDU collaborates with, or you can choose to arrange your stay at another university. SDU collaborates with more than 200 partner universities, and we want to help you find the perfect place for you.

If you start the programme in September, spending your 2nd semester abroad grants you the most flexibility – if you start in February, you get the most flexibility if you spend the 1st semester abroad. Additionally, on the second year of the programme, you have the opportunity to do your Master's thesis project or parts of it abroad.

Read more about spending a semester abroad on MySDU

At the latest when you start the programme, you must fill in and hand in a reflection form in which you explain which skills you want to develop during the actitity to put your main subject into perspective, which elective courses and projects you expect to take, and which advantages/disadvantages there are of your choice.

The reflection is indicative and doesn't bind you to any specific electives. You can expect to receive feedback on your reflection.

If you are applying for admission to start your studies on 1 February, you must, as far as possible, hand in your written reflection before 1 December.

Download reflection form

On the 2nd year of the programme, you will work on your Master's Thesis project, which has a scope of 60 ECTS.

You will typically be affiliated with a research group from the Department of Mathematics and Computer Science, who will be able to counsel and guide you in your literature search and your collection and processing of research data.

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Do you have any questions?

Do you need to know how to apply for a Master's degree programme? Are you in doubt about which programme to choose? Whatever questions you have, we are ready to give you answers and personal guidance.

Write the student counsellors at the Faculty of Science