Each specialisation profile 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.
To the extent possible, we aim to ensure that courses within the same specialisation profile do not overlap in times of classes if you follow the recommended course of study within the standard time limits.
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
- DM840: Algorithms in Cheminformatics (10 ECTS)
- DM841: Heuristics and Constraint Programming for Discrete Optimization (10 ECTS)
- DM886: Cryptographic Engineering (5 ECTS)
- DM892: Approximation and online algorithms (10 ECTS)
Recommended courses in Spring 2024
- DM852: Introduction to Generic Programming (5 ECTS)
- DM872: Mathematical Optimization at Work (5 ECTS)
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
- DM886: Cryptographic Engineering (5 ECTS)
- DM893: Quantum Computing (5 ECTS)
- DM895: Applied Cyber Security (5 ECTS)
Recommended courses in spring 2024
- DM880: Logic for Computer Science (5 ECTS)
- DM883: Distributed systems (5 ECTS)
- DM885: Microservices and Dev(Sec)Ops (10 ECTS)
- Usable Security
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
- DM841: Heuristics and Constraint Programming for Discrete Optimization (10 ECTS)
- DM847: Introduction to Bioinformatics (10 ECTS)
- DM864: Advanced Data Mining (5 ECTS)
- DM873: Deep Learning (10 ECTS)
- DM878: Visualization (5 ECTS)
- DM888: Spatial Data Management (5 ECTS)
- DM894: Advanced topics in data mining and machine learning (10 ECTS)
- DS807: Applied machine learning (10 ECTS)
- DS834: Data Science for the Metaverse (5 ECTS)
- ST813: Statistical Modelling (10 ECTS)
Recommended spring courses
- DM870: Data mining and machine learning (10 ECTS)
- DM871: Linear and Integer Programming (5 ECTS)
- DM872: Mathematical Optimization at Work (5 ECTS)
- DM887: Reinforcement learning (10 ECTS)
- DM890: Computer vision (10 ECTS)
- ST514: Multivariate Statistical Analysis (5 ECTS)
- ST816: Computational Statistics (10 ECTS)
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