Spring semester 2026: Three master level courses offered as electives

Target group for these course is master level students at both the 2-year and 5-year master program. The courses are categorized as elective courses in both these programs and can also be a specialisation for the 5-year program. Exchange students may in certain cases take the course if they have the recommended prerequisites to take it. The courses are not available for bachelor students.

INF-3210 / INF-8210 Energy Informatics - Green Computing
Professor Phuong H. Ha, Department of computer science (UiT) will be responsible for the course.

Course content
The course covers various aspects of green computing, particularly the principles and applications of energy- and resource-efficient computing, including green AI, edge intelligence, and datacenter. It consists of two parts. The first part, "Principles of energy- and resource-efficient computing systems," considers various energy- and resource-efficient techniques across different system stack levels, including computer architecture, runtime systems, libraries, frameworks, and algorithms. The second part, "Leveraging green computing towards sustainable development," considers green computing applications to monitor and reduce the environmental impact of ICT and other segments such as energy.

Course objectives and other course info: https://uit.no/utdanning/emner/emne/906658/inf-3210 | https://uit.no/utdanning/emner/emne/911021/inf-8210
Tentative lecture plan and course timeline: https://tp.educloud.no/uit/timeplan/timeplan.php?id%5B%5D=INF-3210%2C1&type=course&sem=26v&campus=&hide_old=0

For this course a PhD Version of the course is available and can be considered relevant for the PhD training Component. PhD students must register for the exam through the Studentweb within February 1st, 2026.

INF-3600 Generative Artificial Intelligence
Associate professor Helge Fredriksen, Department of computer science and associate professor Benjamin Ricaud, Department of Physics and Technology will be responsible for the course.

Course content
The course will cover Large Language Models (LLM), Generative AI for images, in addition to other modalities like sound. Applied aspects such as continuous integration in production systems will be given attention.

Some emphasis will be put on creating AI tools, which could lead to possible startup ideas.

Overlap

10 ECTS against INF-3993 special curriculm that was offered in the spring semester 2025.
10 ECTS against FYS-3810 special curriculm that Benjamin Ricaud gave in the spring semester 2024.
3 ECTS against INF-8606 Generative AI for health and life sciences

Course objectives and other course info: https://uit.no/utdanning/emner/emne/906659/inf-3600
Tentative lecture plan and course timeline: https://tp.educloud.no/uit/timeplan/timeplan.php?id%5B%5D=INF-3600%2C1&type=course&sem=26v&campus=&hide_old=0

INF-3910-8 Computer Science Seminar: GameLab
Associate professor André Henriksen, Department of computer science (UiT) will be responsible for the course but he also has Ernie Roby-Tomic on the team as well as potensial guest lecturers from the game industry.

Course content
The students will learn the complete cycle of game development from idea to launch by developing a game with user experience and technology good enough that it can be launched as a product.

The students will learn to develop games. The students will choose their own programming languages, game development frameworks, and other technologies in the software stack. The students are encouraged to build on state-of-the-art game engines, SDKs or services for their games.

The course will therefore cover all steps in the game development process:

Design: Create a game design and write a design document.
Technology: Select and reason about the correct technological choices for the designed game taking into account time, resources, technical performance and user experience constraints.
Team: Decide roles and share tasks and responsibilities across a team based on suitable skillset and area of interest.
Process: Agree on the software engineering process, milestones and approach to development.
Development: Implement a complete game in the allocated time that has the required performance and that provides a usable and fun experience for the player.
Business: Launch the game on the target platforms app store with a clear business plan for how and why the game can earn money.

Course objectives and other course info: https://uit.no/utdanning/emner/emne/906662/inf-3910-8
Additional information about the course: https://uit-gamelab.github.io/Spring26/
Tentative lecture plan and course timeline: https://tp.educloud.no/uit/timeplan/timeplan.php?id%5B%5D=INF-3910-8%2C1&type=course&sem=26v&campus=&hide_old=0

Registration
Master level students must register for the exam through the Studentweb within February 1st, 2026 (normal proceedure).

PhD-special curriculum (for Generative AI and GameLab)
If either Generativ AI or GameLab are considered relevant for the PhD training component this special curriculum can also be offered as a PhD special curriculum. The course code is INF-8810. The PhD students must expect an expanded scope / depth in work requirements / exam-related component(s) compared to what is the case for the master's students.

PhD students enrolled at UiT can contact the Department of Computer Science.

Kortnytt fra Institutt for informatikk

Fuglesteg, Jan jan.fuglesteg@uit.no Studierådgiver