You will find detailed course information, list of course literature, schedule and start date at Courses and timetables. Select semester in the drop-down menu and search by course name.


1st Semester

Mandatory courses 4 x 7,5 credits

Enterprise Computing and ERP Systems 7,5 credits

The course discusses how enterprise information systems support organizations in value chains and supply chains. The course introduces a number of modern enterprise modelling techniques based on linguistic instruments and economic ontologies. It is shown how these techniques support requirements elicitation for enterprise information systems design.

Data mining in Computer and System Sciences 7,5 credits

As data is becoming more and more readily available, the need to analyse and make use of these large amounts of data is rapidly growing. Data mining deals with techniques that can find interesting and useful patterns in large volumes of data. This course covers basic concepts, techniques and algorithms in data mining combined with hands-on experimentation.

Introduction to Information Security 7,5 credits

The course is primarily an introductory course that prepares students for advanced studies in the field of information security and digital security. The course therefore provides a general conceptual framework for the subject area and provide familiarity with the terminology that is relevant to the more specialised security and forensics courses offered by the department.

Internet of Things services 7,5 credits

The course covers development of applications, services, and design of communication between clients and interfaces to Internet of Things (IoT) architectures. The course provides an understanding of the design process regarding new communication systems that is specially designed for new context-based IoT applications. The student also get an understanding of the integration of smart objects for IoT.

2nd Semester

Mandatory course 1 x 7,5 credits

Scientific Communication & Research Methodology 7,5 credits

Computing as a discipline combines three academic traditions: the theoretical tradition, the scientific (experimental) tradition and the engineering tradition. Due to that combination, there is no clear methodological tradition in computer science. This course introduces how to design, implement and report a research study. The main focus of this course is research design and reporting. Students will learn how to align problem statement, aims, objectives, research questions, data collection and analysis, and reporting into a coherent and logically flowing whole.

Elective courses 3 x 7,5 credit
From Master elective courses spring

3rd Semester

Mandatory course 7,5 credits

Research Methodology for Computer and Systems Sciences 7,5 credits

Course deals with research strategies (case studies, experiments and survey), methods for data collection (questionnaires, interviews and observations) and software-based analysis (thematic, conversation and interaction analysis). Statistical and mathematical methods include descriptive and inferential statistics. Evaluation of data is included.

Elective courses 3 x 7,5 (30) credits 

From Master elective courses autumn
or Exchange studies info regarding exchange studies

4th Semester

Master Thesis 30 credits
More information about Master Thesis


The courses may change depending on the academic staff of DSV.