Master's Programme in Computer and Systems Sciences
Designed for future IT leaders, our programme equips you with advanced knowledge in computer and systems sciences. Beyond theory, we focus on practical application, ensuring you graduate ready to design, manage and innovate within complex digital systems.
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 consists of both compulsory and elective courses. In addition to the core courses, you will choose from a pool of electives. This gives you the opportunity to tailor your studies according to your interests.
Among the elective courses you will find courses in data mining, information security, business intelligence, digital games, decision analysis and IT project management. Additionally, you learn about scientific communication and research methodology.
You will find detailed course information, list of course literature, schedule and start date on the course information page at "Courses and timetables". Select semester in the drop-down menu and search by course name.
Courses and timetables
Year 1
1st Semester
Mandatory courses 4 x 7.5 credits
Enterprise Computing and ERP Systems 7.5 credits
Foundations of Data Science 7.5 credits
Introduction to Information Security 7.5 credits
Internet of Things Services 7.5 credits
2nd Semester
Mandatory course 1 x 7.5 credits
Research Methodology in Computer and Systems Sciences 7.5 credits
Elective courses 3 x 7.5 credits
Year 2
3rd Semester
Elective courses 4 x 7.5 credits
Master elective courses autumn
For this semester, you have the possibility to apply for exchange studies.
Exchange studies
4th Semester
This program starts each autumn semester.
Please note that it is only possible to apply for this programme in the first admission round (mid-October to mid-January). The programme is not open for admission in the second admission round.
Find answers to the most common questions regarding application, requirements and study format (distance or campus). FAQ Master's programmes
Selection process
The selection is made from the following three criteria:
- Grades of academic courses,
- mandatory motivation letter and
- the relevance of previous studies in relation to the programme.
It is therefore very important to submit a motivation letter.
Find instructions for the motivation letter below.
Required supporting documentation
Motivation letter
The letter shall include:
- Tell us something about yourself. Who are you?
- Motivate why you want to study this programme.
- Describe how you fulfil the entry requirements of 90 ECTS within computer and systems sciences (e.g., computer science, systems science, informatics, information systems etc.)
Maximum one A4 page.
Save the letter as “Motivation letter SCSSO”.
Submit the letter together with your application at universityadmissions.se
Build your own focus
You can either pick and mix courses that interest you, or explore our suggested course combinations if you want to focus on a specific subject area.
You do not need to take all the courses within a group, and you are free to combine courses from different groups. There are also other subjects and courses to choose from that are not included in the groups below, such as decision analysis, quantum programming, IT project management, databases, business intelligence and entrepreneurship.
The choice is yours!
Here you can find the full range of elective courses:
Elective courses autumn
Elective courses spring
Suggested course combinations
Data Science
Spring 2nd semester
Natural Language Processing 7.5 credits – NLP
Machine Learning 7.5 credits – ML
Autumn 3rd semester
Research Topics in Data Science 7.5 credits – RTDS
Reinforcement Learning 7.5 credits – RILE
Explainable AI 7.5 credits – XAI
Digital Games
Information and curriculum for the courses in digital games will be available soon.
The courses will start in the spring of 2027.
Spring 2nd semester
Reading course about games 7.5 credits
GPU architectures and real time computing 7.5 credits – GPU
Inclusive game development 7.5 credits – IGDEV
Autumn 3rd semester
AIBU Theory 7.5 hp
Applied distributed Internet of Things (IoT)
Spring 2nd semester
Parallel and distributed programming 7.5 credits – PARADIS
Autumn 3rd semester
Distributed data processing for Ubiquitous computing 15 credits – DUC (entry requirements: Parallel and distributed programming 7.5 credits – PARDIS)
Tiny Machine Learning 7.5 credits – TINYML
Security
Spring 2nd semester
Network Security 7.5 credits – NETSEC
Cyber Security 7.5 credits – CYBER
Cyber Forensics 7.5 credits – CYFO
Autumn 3rd semester
Digital Forensics 7.5 credits – DIFO
Information Security in Organisations 7.5 credits – SECORG
Degree
Find the degree awarded for this programme in the syllabus, either in the right sidebar (desktop) or below (mobile device).
Please note, that you can only be awarded one bachelor’s degree, one master’s degree (60 credits) and one master’s degree (120 credits) in computer and systems sciences from our department.
Research
Research subjects at the department with relevance to the program:
AI and Data Science
Business Process Management and Enterprise Modelling
Cyber Security
Digital Games and Simulation
Human–Computer Interaction
Language Technology
Risk and Decision Analysis
Technology Enhanced Learning
Graduates of the Master's programme in Computer and Systems Sciences are highly sought after for roles in both traditional and emerging fields, such as:
- Core tech roles include system designer and developer, security expert, and IT project manager.
- Specialised fields include architect for distributed intelligent IoT systems, or designer for simulation and game systems.
The programme also serves as a direct pathway to PhD studies for a future career in academic or industrial research, particularly in areas such as decentralised AI or human–computer interaction.
