Established by: Faculty Board of Science and Technology, 2021-10-25
Revised by: Faculty Board of Science and Technology, 2023-02-27
Contents
The student practices their ability to specify, plan, perform, and present an independent work that contributes to the formation of knowledge. Through their work, the student integrates previous knowledge and immerses themselves in at least one Computing Science topic in Artifical Intelligence. The result of the work is presented in English both orally and in writing.
The course is partitioned into two modules.
Module 1. Independent work (28 credits) The student performs the degree project as an independent work, either within the scope of a research project at the university or a development project in industry. The work shall concern some form of problem solving and lead to the formation of new knowledge. Therefore, it must not only consist of routine programming. The work must lead to subject specialization in relation to some previously completed course on the advanced level. The specialization shall be within a Computing Science topic in Artificial Intelligence and be of relevance to the independent work.
Module 2. Presentation (2 credits) The student presents their work in writing, in the form of a scientific report, and defends it orally, in the form of a public seminar. The student will also dispute someone else's work.
Expected learning outcomes
Knowledge and understanding After completing the course, the student should be able to:
(FSR 1) demonstrate significantly in-depth knowledge in at least one Computing Science topic in Artificial Intelligence
Competence and skills After completing the course, the student should be able to:
(FSR 2) critically, independently, and creatively identify, formulate, and manage a complex question at issue
(FSR 3) participate in research or development and thereby contribute to the formation of new knowledge in a Computing Science topic in Artificial Intelligence
(FSR 4) plan and with scientific or engineering methods perform qualified tasks within given time frames
(FSR 5) critically and systematically integrate knowledge
(FSR 6) clearly argue for their conclusions, both orally and in writing
(FSR 7) independently search for information and evaluate the relevance of information relative to the question at issue
Judgement and approach After completing the course, the student should be able to:
(FSR 8) evaluate master's theses based on relevant scientific, societal, and ethical aspects
(FSR 9) judge their own competence and suitability to pursue a specific master's thesis topic
Required Knowledge
To be admitted you must have a Bachelor's Degree and courses at the advanced level corresponding to 60 ECTS-credits out of which at least 30 ECTS must be in Computing Science and include the following seven courses (or equivalent): 1) Fundamentals of Artificial Intelligence (5DV124), 2) Artificial Intelligence - Methods and Applications (5DV181), 3) Machine learning (5DV194), 4) Responsible Design of Interactive AI-Systems (5DV211), 5) Fundations of Logic and Model Theory (5DV102), or Statistics for Engineers (5MS069) 6-7) at least three courses within one of the profiles in Computing Science in the Master program in Artificial Intelligence, se current programme syllabus.
Depending on the focus of the Degree Project some extra prerequisites might be needed.
Proficiency in English equivalent to the level required for basic eligibility for higher studies.
Form of instruction
The teaching consists of independent work with individual supervision by a supervisor appointed by the department. The student is responsible for maintaining regular contact with the supervisor and manage their resources. If the work is external, then the external party will also appoint a supervisor.
Examination modes
Examination of Module 1. Independent work The module encompasses FSR 2, 3, 4, 7, 9. The module uses the grade scale Fail (U), Pass (G). The assessment is carried out through an ongoing examination consisting of a written project plan submitted in connection to the planning of the work and a written project diary created during the project. Through an ongoing assessment of these documents, the examiner decides if the student has reached the module's expected learning outcomes or not.
Examination of Module 2. Presentation The module encompasses FSR 1, 5, 6, 8. The module uses the grade scale Fail (U), Pass (G), Pass with distinction (VG). The assessment is carried out through a combination of three tests:
An oral and written critique of someone else's work.
An oral presentation of the student's own work.
A written report of the student's own work and the subject specialization.
Grade on the course The course uses the grade scale Fail (U), Pass (G), Pass with distinction (VG). When both modules are passed, then the grade on the course is set to the same as the grade on Module 2.
Adapted examination The examiner can decide to deviate from the specified forms of examination. Individual adaptation of the examination shall be considered based on the needs of the student. The examination is adapted within the constraints of the expected learning outcomes. A student that needs adapted examination shall no later than 10 days before the examination request adaptation from the Department of Computing Science. The examiner makes a decision of adapted examination and the student is notified.
Other regulations
A student may request (but not demand) extra supervision resources past the end of the course. The request should be sent to the study director at the Department of Computing Science.
This course may not be included in a degree, in whole or in part, at the same time as another course with similar content. In case of doubt, the student should consult the study counsellor at the Department of Computing Science and/or the programme coordinator for their degree programme.
If the syllabus has expired or the course has been discontinued, a student who at some point registered for the course is guaranteed at least three examinations (including the regular examination) according to this syllabus for a maximum period of two years from the syllabus expiring or the course being discontinued.
Literature
Valid from:
2024 week 1
The literature is determined by the topic of the thesis.
