Computer Science - Master of Science Degree Programme

The master’s programme in Computer Science at UiS is open to Norwegian and international students. With a Master’s in Computer Science, the door is open to some of the most challenging and interesting jobs in the field. The study programme gives a broad foundation within the field of computer science. The study programme has two specialisations: (1) Reliable and Secure Systems and (2) Data Science.

This in an international study programme and all courses are given in English. The programme is organised under the Faculty of Science and Technology, Department of Electrical Engineering and Computer Science. A completed master’s degree in Computer Science provides the basis for admission to PhD studies within information technology, mathematics and physics. 

Programme content, structure and composition 

After the student has been admitted to the two-year master's programme in Computer Science, the student must take a test in programming and system administration. If the student does not pass the test, UiS will offer and encourage the student to complete a preparatory summer course in programming and system administration. The purpose of the course is that the students should be best prepared for the master's program. The course takes place in early August, before the regular semester starts.

The University of Stavanger does not consider it necessary to offer summer courses for those students who have already passed the following courses at the University of Stavanger:

• 10 ECTS in programming and at least 5 ECTS in operating systems

The University of Stavanger offers a master's programme aimed at students who have completed a 3-year engineering degree in computer technology. The two-year master's degree in Computer Science comprises 120 ECTS.

The programme has practical courses that build on mathematics, statistics, and basic computer science subjects from the bachelor's degree in Computer Science. The program contains advanced statistics topics and algorithmic topics, machine learning and data intensive systems. The specialisation Reliable and Secure Systems will have topics in network security, distributed systems and algorithm theory. The specialisation Data Science will specialize in information retrieval, data recovery and further specialisation in statistics.

The programme offers a variety of work and teaching programs, from traditional lecture series and exercises, project work, self-study and laboratory teaching to introduction and practice in the use of modern software. The emphasis on the individual teaching forms varies to some extent between the different subject groups.

The following is described in the individual course description:

- Forms of work and teaching

- Evaluation Forms

- Syllabus

- Assessment

The university emphasizes being able to offer all the studies as planned but must make reservations about sufficient resources and / or students to complete the offer. Over time, it will be natural for the academic content and offering of courses to change due to the general developments in the field of study, the use of technology and changes in society at large.

After admission to the programme, you can apply for a part-time study programme. Alternatively, you can apply directly to a part-time study.

Learning outcomes

After having completed the master’s programme in Computer Science, the student shall have acquired the following learning outcomes, in terms of knowledge, skills and general competences:

Knowledge

K1: Have advanced knowledge in information technology with specialization in either reliable and secure systems or data science.

K2: Have deep knowledge in the subject areas’ scientific theories and methods.

Skills

S1: Use relevant methods for research and software development in an independent manner.

S2: Analysze and relate in a critical manner to different information sources and apply these to structure and formulate professional reasoning within information technology.

S3: Perform an independent, limited research- or development project under guidance and in line with established ethical norms for research.

S4: Exploit knowledge in wireless communication, sensor networking, and distributed communication systems. (Reliable and Secure Systems)

S5: Design, model, simulate, and develop advanced network based computer systems with focus on dependability and security. (Reliable and Secure Systems)

S6: Develop data analysis applications for specific data sets and tasks or processes. (Data Science)

S7: Model problems and develop new instruments and applications for data collection, analysis and management following established engineering principles. (Data Science)

S8: Evaluate instruments and applications to optimize data collection, analysis and management. (Data Science)

General Competence

G1: Analysze relevant professional, and research ethical problems.

G2: Apply one’s knowledge and skills to new areas to conduct complex tasks and projects.

G3: Communicate comprehensively about own work, and master the subject area’s form of expression.

G4: Communicate professional problems, analyse, and draw conclusions within the subject area, both with specialists and the general public.

Career prospects

Researchers and developers in Computer Science are indispensable in almost all industries. Some examples of businesses where they find employment are: consulting companies, telecommunications companies, oil-related businesses, hospitals and other public agencies. We encounter digital technology everywhere, and researchers and developers in Computer Science are crucial in making information society a reality.

Specialisation: Reliable and Secure Systems

Specialisation in Reliable and Secure Systems provides a basis for work in the development and planning of commercial computer systems for different purposes. It builds knowledge and skills in network security, reliability of distributed systems, and simulation and modeling.

Specialisation: Data Science

Specialisation in Data Science provides a basis for work in data analysis and development of data processing systems for the whole data lifecycle. It builds knowledge and skills in advanced statistics, data mining, machine learning and processing of large data volumes.

A completed master’s degree in Computer Science provides the basis for admission to the PhD programme in Information technology, mathematics and physics

Course assessment

Schemes for quality assurance and evaluation of studies are stipulated in the Quality system for education