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Master Programme in Computer and Systems Sciences

  • 120 credits

This programme offers you the opportunity to expand your knowledge in IT Systems. You will not only learn the theories, methods and tools but also learn how to practice.

You will learn how to efficiently develop advanced computer systems and software systems using both agile and standard system development methods.

The programme helps you to develop soft skills along with technical skills such as understanding the needs of users, practicing in group dynamics and project management. The Programme is to a large extent project and problem oriented.

This programme is very diverse and offers you the opportunity to select from a variety of courses. Among the elective courses you will find courses in data mining, IT management, information security, business intelligence, decision analysis and IT project management. Additionally, you learn about scientific communication and research methodology. 

  • Programme overview

    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.

    Year 1

    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 provides 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 credits
    From master elective courses spring

    Year 2

    3rd Semester

    Mandatory course 1 x 7,5 credits

    Research Methodology for Computer and Systems Sciences 7,5 credits
    The 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 credits 

    From master elective courses autumn or exchange studies information regarding exchange studies

    4th Semester

    Master thesis 30 credits

    More information about master thesis

  • How to apply

    Find answers to the most common questions regarding application, requirements and study format (distance or campus) here

    Selection process

    Additional eligibility criteria

    The selection of students is based on grades of academic courses. This means that you don’t have to submit recommendation letters or motivation letter when applying to this specific programme.

  • Career opportunities

    The programme is suitable for students aiming to become system designers, system developers, security experts and IT project managers. Graduates may also enter Ph.D. programmes to pursue career in research.

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