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 area of specialization 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 have further academic preconditions. Please see the individual course descriptions.
Recommended autumn courses
- DM817: Network Programming: Theory and Applications (10 ECTS)
- DM840: Algorithms in Cheminformatics (10 ECTS)
- DM841: Heuristics and Constraint Programming for Discrete Optimization (10 ECTS)
- DM860: Online algorithms (10 ECTS)
- MM855: Introduction to Graph Theory(5 ECTS)
- MM856: Graph theory (10 ECTS)
Recommended spring courses
We recommend that you choose either DM871: Linear and Integer Programming (5 ECTS) or DM872: Mathematical Optimization at Work (5 ECTS).
Additionally, we recommend that you choose from among the following courses:
- DM803: Advanced data structures (10 ECTS)
- DM846: Logic for Computer Science (10 ECTS)
- DM852: Introduction to Generic Programming (5 ECTS)
- DM891: Algorithms under Stochastic Uncertainty (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 profile 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.
Recommended autumn courses
- DM885: Microservices and Dev(Sec)Ops (10 ECTS)
- DM886: Cryptographic Engineering (5 ECTS)
Recommended spring courses
- DM861: Concurrency Theory (10 ECTS)
- DM880: Logic for Computer Science (5 ECTS)
- DM883: Distributed systems (5 ECTS)
Examples of previous thesis project titles
- Foundational aspects of choreographic programming
- A formal programming model for Bitcoin transactions
- Packaging microservices
Data Science is concerned with managing and analysing data in order to generate knowledge and insights. The field spans areas such as statistics, visualisation, machine learning, data mining, deep learning, and optimisation. A key application of data science is in artificial intelligence, where data‑driven insights are used to address challenges faced by modern society.
In many sectors, drawing on data‑based insights can make a significant difference. Everyday examples include product recommendations in online shops or the personal assistants built into smartphones.
Numerous companies use data to optimise their production and business operations, and an increasing number of devices incorporate machine learning, optimisation, and artificial intelligence — including washing machines, vacuum cleaners, drones, self‑driving cars, and other types of robotics.
Most of the courses we offer in Data Science and AI require a basic understanding of linear algebra. Not all courses are offered every year.
Recommended autumn courses
- DM885: Microservices and Dev(Sec)Ops (10 ECTS)
Recommended spring courses
- DM861: Concurrency Theory (10 ECTS)
Examples of previous thesis project titles
- Simulation of Traffic Flow in a Real Urban Network
- Optimization of coordinated traffic signal intersections
- Flight Planning in Free Route Airspaces
- Artificial intelligence in action real-time strategy games
- Optimizing heat and power production using column generation
Any questions?
The student counsellors at the Faculty of Science are ready to help you with your study-related questions.
Contact the student counsellors at the Faculty of Science