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Høst 2023

FYS-2021 Machine Learning - 10 stp


The course is administrated by

Institutt for fysikk og teknologi

Type of course

The course is available as a singular course. The course is also available to exchange students and Fulbright students.

Course contents

The course will introduce the students to the fundamental concepts in machine learning and will study widely used and popular machine learning algorithms for analysing data in the modern society. The course will cover elementary methods for both supervised and unsupervised learning, both for regression and classification. Supervised methods will include technologies such as decision trees, linear discrimination and neural networks. TUnsupervised methods covered will include machine learning methods based on linear algebra as well as standard clustering methods. The course will have a significant practical component, in which various applications will be treated in the form of case studies.

Admission requirements

Generell studiekompetanse eller realkompetanse + SIVING

Local admission, application code 9391 - enkeltemner i ingeniørfag.


Objective of the course

Knowledge - The student is able to:

Skills - The student is able to:

General expertise - The student is able to:


Language of instruction

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

Exercises : 30 hours