Entry requirements

1. Bachelor of Science in computer science or related subjects such as mathematics, informatics, telecommunications, electrical engineering, physics. 2. At least 15 credits in programming. 3. At least 7.5 credits in mathematics. 4. Knowledge equivalent to English 6 at Swedish upper secondary level. 5. At least 45 credits completed in the main area of study within the master programme, Computer Science: Applied Data Science including the course Research Methods of Computer Science and Fundamental Computational Theory (DA634E)

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 consists of three parts: problem definition and project planning; the thesis project; and the opposition on another degree project The thesis project has two phases: - To perform the project and document it in writing (in the form of the degree project), and - To present and defend the thesis verbally The opposition consist of carefully studying and critically analysing another student's degree project, producing a written opposition and acting as an opponent in the presentation of another student's degree project.

Learning outcomes

Knowledge and understanding For a passing grade the student shall be able to: 1\. Demonstrate in-depth knowledge of computer science with a special focus on Data Science. 2\. Explain the research process and its planning Competence and abilities For a passing grade the student shall be able to: 3\. Independently and creatively identify, formulate and handle complex problems 4\. Plan and perform research and development projects within predetermined time frames 5\. Describe a research project's contribution to an area of knowledge 6\. Actively seek and find relevant information on a specific research problem 7\. Apply research methods 8\. Verbally and in writing present the results of a research project in a scientific manner in international and national contexts. 9\. Communicate results of a research project to different target groups 10\. Critically analyse a scientific report and identify its main strengths and weaknesses Evaluation abilities and approach For a passing grade the student shall be able to: 11\. choose a research method for a specific scientific problem and provide arguments as to suitability 12\. assess and analyse relevant research issues of importance for data science 13\. make data science deliberations based on scientific, societal and ethical aspects 14\. demonstrate an insight into the opportunities and limitations of science, the role these play in society and the population’s responsibility for how this is applied 15\. demonstrate the ability to identify his or her own need for further knowledge and to take responsibility for his or her own knowledge development.

Learning activities

The teaching is project-based and adapted to the student's previous knowledge, ability, and experience. The main activities are thesis work, supervision and seminars. The student will also present orally and act as an opponent on another thesis. The supervisor who is assigned to the student (and any external contact person, for example a user of the project result) supports and guides the student through the project, but it should be the student who initiates any request for support. The student is expected to report to the supervisor on an ongoing basis during the project work.

Assessment

Students' performance is assessed through: - Project plan (3 credits, UG) – learning outcomes 2,3,4,5,6,7,11,15 - The written thesis (25 credits, UA) – learning outcomes 1,2,3,4,5,6,7,8,9,11,12,13,14,15 - An oral presentation (1 credit, UG) – learning outcomes 8, 9 - Written and oral opposition (1 credit, UG) – learning outcome 10 For a passing grade (at least E), all parts of the course must be approved. The final grade of the course is based on the grade for the thesis and the written presentation.

Course literature

- Dawson, Christian (2009). Projects in computing and information systems. A student’s guide, 2nd edition. Addison Wesley - Oates, B.J. (2005). Researching Information Systems and Computing. Sage Publications, UK - Zobel, J. (2004). Writing for Computer Science – The art of effective communication, 2nd edition. Springer, UK - Individual literature is selected by the student in consultation with the supervisor

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.