spring 2026
INF-3210 Energy Informatics - Green Computing - 10 ECTS

Type of course

The course can be taken as a singular master-level course.

Admission requirements

Higher Education Entrance Requirement + Bachelor's degree in Computer Science or similar education. The Bachelor degree must contain a specialization in Computer Science worth the equivalent of not less than 80 ECTS credits. Application code: 9371 - Singular courses at master's level.

Course overlap

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

INF-8210 Energy Informatics - Green Computing 8 ects
INF-3910-2 Computer Science Seminar: Green Computing 10 ects

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.

Recommended prerequisites

INF-0101 Introduction to Programming, INF-0102 Computational Programming, INF-0103 Computer Fundamentals and Programming, INF-1049 Introduction to computational programming, INF-1100 Programming fundamentals, INF-2201 Operating system fundamentals, MAT-1005 Discrete Mathematics

Objectives of the course

Knowledge - the student has

  • knowledge of the main topics of green computing at an introductory level
  • knowledge of the central challenges of green computing
  • knowledge of applications of energy- and resource-efficient computing systems, including Green AI and edge intelligence
  • knowledge of leveraging computing systems towards sustainable development (e.g., energy-efficient data centers, observation systems for sustainable development, smart power grid)

Skills - the student can

  • design and analyze algorithms and protocols for energy efficiency
  • select development environments and tools to develop energy-aware applications and systems towards sustainable development
  • present and discuss energy- and resource-aware computing systems and applications

General competence - the student know

  • how to read literature, extract information from it, and present it coherently in public
  • how to conduct technical reviews and come up with critiques to current solutions to open problems
  • how to write technical reports

Language of instruction and examination

The language of instruction is English, and all of the syllabus material is in English. Examination questions will be given in English but may be answered either in English or a Scandinavian language.

Teaching methods

Lectures: 30 hours, Colloquium: 30 hours, Laboratory guidance: 30 hours. These include review and critique of scientific papers, conducting experimental studies, and writing technical reports.

Information to incoming exchange students

This course is available for inbound exchange students.

This course is open for inbound exchange student who meets the admission requirements, including prerequisites. Please see the Admission requirements" and the "Prerequisite" sections for more information.

Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412.


Schedule

Examination

Examination: Duration: Grade scale:
Off campus exam 5 Weeks A–E, fail F

Coursework requirements:

To take an examination, the student must have passed the following coursework requirements:

Up to 3 written/oral assignments Approved – not approved
UiT Exams homepage

Re-sit examination

No re-sit exam.
  • About the course
  • Campus: Tromsø |
  • ECTS: 10
  • Course code: INF-3210
  • Earlier years and semesters for this topic