Schedule, syllabus and examination date

Choose semester

Course content

Bayesian decision theory, supervised learning, parametric and non-parametric methods, linear discriminant functions, feature extraction, unsupervised learning, cluster analysis, syntactic methods.

Learning outcome

The course is an introduction to classification theory and pattern recognition. The students are provided with sufficient knowledge for designing and evaluating classifiers using proper methods for the problem at hand.


Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.


Formal prerequisite knowledge


Recommended previous knowledge

MAT1120 – Linear Algebra MAT1110 – Calculus and Linear Algebra STK1000 – Introduction to Applied Statistics

Overlapping courses

STK4030 "Modern Data Analysis", 8 credits.

UNIKI385, 8 credits.


3 hrs. lectures and exercises per week. There will be mandatory assignments that need to be approved in order to attend the exam.


Oral exam at the end of the semester. In case of many students, there may be held a written exam.

In order to take the exam, mandatory assignments needs to be approved.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Explanations and appeals

Resit an examination

Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.

Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.

Facts about this course






Every autumn


Every autumn

Teaching language