Programme structure
The master’s programme comprises 120 ECTS and has the following structure:
- mandatory courses, 30 or 50 ECTS credits, depending on type of master's thesis
- elective courses, 30 or 40 ECTS credits, depending on type of master's thesis
- master's thesis, 30 or 60 ECTS credits
Course of study
Example with long master's thesis of 60 ECTS credits:
| 4th semester | Master's thesis | Master's thesis | Master's thesis |
|---|---|---|---|
| 3rd semester | Elective course | Master's thesis | Master's thesis |
| 2nd semester | Elective course | Master's thesis | |
| 1st semester | Core course | Elective course | |
| 10 ECTS credits | 10 ECTS credits | 10 ECTS credits |
Example with short master's thesis of 30 ECTS credits:
| 4th semester | Master's thesis | Master's thesis | Master's thesis |
|---|---|---|---|
| 3rd semester | Elective course | Elective course | Elective course |
| 2nd semester | Core course | Elective course | |
| 1st semester | Core course | Core course | |
| 10 ECTS credits | 10 ECTS credits | 10 ECTS credits |
The tables above shows a general illustration of how a course of study can be organized. You can choose to structure your course of study differently if this is more expedient for you.
Note: Students normally complete coursework before the final semester. The last semester is intended to be reserved for the final 30 ECTS of thesis work.
Courses and master's thesis
During the first semester, you choose courses and the topic of your master's thesis in collaboration with your supervisor.
Mandatory courses
In the programme option Language Technology you must complete two mandatory courses (20 ECTS):
In addition, you must complete at least 10 ECTS (students with long master’s thesis) or 30 ECTS (students with short master’s thesis) from the list of core courses below. Core courses are the most fundamental and specialised courses for your programme option.
Core courses
IN4030 – Introduction to Bioinformatics IN4050 – Introduction to Artificial Intelligence and Machine Learning IN4060 – Semantic Technologies IN4120 – Search Technology STK-IN4300 – Statistical Learning Methods in Data Science IN4310 – Deep Learning for Image Analysis IN-STK5000 – Responsible Data Science IN5010 – Design, Technology and Society IN5310 – Advanced Deep Learning for Image Analysis IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems IN5640 – Developing Large Language Models
Elective courses
You can choose additional elective courses from the list of core courses, or choose other courses.
Up to a limited amount of non-informatics coursework may be included when academically relevant and recommended by the supervisor.
Master's thesis
In the master's thesis you will have the opportunity to explore a linguistic problem in depth and convey the results in writing and verbally.
Your work with the master's thesis will be divided over several semesters. The last semester of the master's programme should be used exclusively for the final 30 ECTS of the thesis project. The submission of the master's thesis is done on a fixed date in the last semester. The master's thesis must be presented publicly at the end of the semester. Following the presentation, there will be an oral examination with the sensors and supervisor about the thesis.
The master's thesis is an independent research work within a subject that is to be conducted under close supervision. You are supervised by members of either the Language Technology Group (LTG), Scientific Computing and Machine Learning (SCML) or Digital Signal Processing and Image Analysis (DSB), but you can also choose to write your thesis in collaboration with a company or research center.
Progression requirements
The standard study time for the master's programme is two years, or four years if you apply for part-time studies. If you spend more time than two years, it is important that you familiarise yourself with the policies for admission and your right to study. Your right to study may be cancelled if you do not register for the first semester of the study programme and you have absence without valid reason for more than one semester.
Recognition of master's courses from former education
If you are admitted to the master's programme and you have completed master's courses outside the University of Oslo, you may apply to have these courses recognised as part of your degree. Please contact the Department of Informatics for more information.
Honours certificate
Are you academically ambitious? It is possible to supplement your master's degree with an honours certificate worth 20 credits. You take the certificate concurrently with the master's programme.
Diploma and degree
The diploma is issued when you have completed the courses that meet the requirements for a degree. Read more about diplomas.