Skip to main content

ID2000 Machine Learning 6.0 credits

This course will give the student a good fundamental knowledge about the field of Machine Learning: the study of artifacts, in particular algorithms that improve their performance with experience. The course will discuss the character of what is learned, properties of basic algorithms, issues of representation and general problems that have to be handled independent of representation and choice of algorithms. Some special emphasize will be given to the two specific technical areas: inductive logic programming and genetic algorithms.

Course offering missing for current semester as well as for previous and coming semesters

Content and learning outcomes

Course contents

No information inserted

Intended learning outcomes

No information inserted

Course disposition

No information inserted

Literature and preparations

Specific prerequisites

No information inserted

Recommended prerequisites

No information inserted


No information inserted

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F


No information inserted

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted


No information inserted

Further information

Course web

No information inserted

Offered by

ICT/Systems Science (SU)

Main field of study

Information Technology

Education cycle

Second cycle

Add-on studies

No information inserted