Entry requirements

1. Bachelor of Science (at least 180 higher education credits) in computer science or related subjects such as mathematics, informatics, telecommunications, electrical engineering, physics. 2. Knowledge equivalent to English 6 at Swedish upper secondary level. 3. At least 15 credits in programming. 4. At least 7.5 credits in mathematics.

Progression level in relation to degree requirements

The course is part of the programme Computer Science: Applied Data Science, master’s programme, and can be included in the master's degree in computer science (120 credits).

Course contents

The course includes the following elements: - Formulation of scientific problems and hypotheses - Selection of research methods to tackle scientific problems - Scientific publishing: procedure and terms - Basic computational and complexity theory - Research ethics - Science theory and history

Learning outcomes

Knowledge and understanding For a passing grade the student shall be able to: - Describe fundamental scientific approaches - Describe the peer-review procedure for scientific publication and weighting of publications - Place computer science questions and research problems in relation to the general academic tradition - Describe computational and complexity theory foundations of computer science Competence and abilities For a passing grade the student shall be able to: - Formulate a scientific problem - Find and evaluate relevant information for a scientific problem - Analyze results using appropriate statistical methods - Determine what types of tasks are theoretically possible with computing machines and what is their relative difficulty and complexity - Present results in a scientific manner Evaluation abilities and approach For a passing grade the student shall be able to: - Identify his or her need for further knowledge in the field and take responsibility for developing this knowledge - Discuss the opportunities and limitations of science, research ethics, the role of science in society and people’s responsibility for how it is applied - Evaluate the level of science in statements and evidence

Learning activities

Lectures, seminars.

Assessment

The students’ performance is assessed partly from written assignments (5 credits, assessed as pass/fail), and partly from written examination (2.5 credits, assessed as A-E) A passing grade requires a pass in both assignments and the written examination. The final grade is based on the examination.

Course literature

- Oates, B.J., (2005). Researching Information Systems and Computing. Sage Publications, UK. - Roughgarden,T (2020). Algorithms Illuminated (Part 4): Algorithms for NP-Hard Problems, Soundlikeyourself Publishing, LLC. - Zobel, J. (2004). Writing for Computer Science -The art of effective communication, 2nd edition. Springer, UK. In addition to the above-mentioned literature, a collection of scientific articles will be added.

Course evaluation

The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).

Interim rules

When a course is no longer given, or the contents have been radically changed, the student has the right to re-take the examination, which will be given twice during a one year period, according to the syllabus which was valid at the time of registration.

Additional information

If a student has a Learning support decision, the examiner has the right to provide the student with an adapted test, or to allow the student to take the exam in a different format. The syllabus is a translation of a Swedish source text.