STK2100 – Machine Learning and Statistical Methods for Prediction and Classification

Schedule, syllabus and examination date

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Changes in the course due to coronavirus

Autumn 2020 the exams of most courses at the MN Faculty will be conducted as digital home exams or oral exams, using the normal grading scale. The semester page for your course will be updated with any changes in the form of examination.

See general guidelines for examination at the MN Faculty autumn 2020.

Course content

STK2100 gives an introduction to different methods for supervised learning (regression and classification). The course contains both model and algorithm based approaches. The main focus is supervised learning, but also unsupervised methods like clustering will be briefly discussed. The course also deals with issues connected to large amounts of data (’big data’). The course gives a good basis for further studies in statistics or Data Science, but is also useful for students who need to perform data analysis in other fields.

Learning outcome

After completing the course you:

  • know the fundamental principles for supervised learning (regression and classification), and also how to evaluate such methods;
  • can master many different methods for supervised learning, including linear models, logistic regression, tree-based methods, bootstrapping and other simulation-based methods, dimension reduction and regularization, bagging and boosting and support vector machines;
  • have knowledge on issues connected to high-dimensional data;
  • have knowledge of problems connected to large amounts of data and methods for unsupervised learning.

Admission to the course

Students at UiO register for courses and exams in Studentweb.

Special admission requirements

In addition to fulfilling the Higher Education Entrance Qualification, applicants have to meet the following special admission requirements:

  • Mathematics R1 (or Mathematics S1 and S2) + R2

And in addition one of these:

  • Physics (1+2)

  • Chemistry (1+2)

  • Biology (1+2)

  • Information technology (1+2)

  • Geosciences (1+2)

  • Technology and theories of research (1+2)

The special admission requirements may also be covered by equivalent studies from Norwegian upper secondary school or by other equivalent studies (in Norwegian).

STK1100 – Probability and Statistical Modelling, STK1110 – Statistical Methods and Data Analysis, MAT1100 – Calculus, MAT1110 – Calculus and Linear Algebra, MAT1120 – Linear Algebra, IN1900 – Introduction to Programming with Scientific Applications and MAT-INF1100 – Modelling and Computations.

Overlapping courses


3 hours lectures and 2 hours exercise sessions every week of the semester.


2-4 mandatory assignments.

Final written examination.

Examination support material

Approved calculator and formula lists for STK2100.

Information about approved calculators (Norwegian only)

Language of examination

Subjects taught in English will only offer the exam paper in English. You may write your examination paper in Norwegian, Swedish, Danish or English.

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.

Resit an examination

This course offers both postponed and resit of examination. Read more:

Special examination arrangements, use of sources, explanations and appeals

See more about examinations at UiO

Last updated from FS (Common Student System) Nov. 24, 2020 7:20:23 PM

Facts about this course

Teaching language
Norwegian (English on request)