DM825: Introduction to Machine Learning (5 ECTS)

STADS: 15008601

Master's level course

Teaching period
The course is offered in the autumn semester.
The course is offered when needed.

Teacher responsible
Marco Chiarandini, Lektor,
Tlf.: 6550 4031 Email:

Group Type Day Time Classroom Weeks Comment
Common I Monday 08-10 IMADA Seminarrum 05-11
Common I Wednesday 16-18 Spørg underviseren 05-11
Common I Friday 08-10 IMADA Seminarrum 05-11
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Ubegrænset deltagerantal. 3. kvartal.


Academic preconditions:
The content of the courses DM527 Mathematical Tools, MM501 Calculus I, MM502 Calculus II, DM502 Programming A, DM503 Programming B and MM505 Linear algebra is assumed to be known.

Course introduction
The goal of the course is to give to the students an introduction to techniques for learning from data.

The aim of machine learning is to build computer systems that can adapt to their environments and learn form experience. Learning techniques and methods from this field are successfully applied to a variety of learning tasks in a broad range of areas, including, for example, spam recognition, text classification, gene discovery, financial forecasting.
The course will give an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as linear regression and classification and ending up with topics such as decision trees, boosting, Bayesian networks, neural networks, support vector machines and hidden Markov models.
The course will give the student the basic ideas and intuition behind these methods, as well as a more formal statistical and computational understanding. Students will have an opportunity to experiment with machine learning techniques in R and apply them to a selected problem.

Expected learning outcome
At the end of the course the student will be able to:

  • recognize which learning method is suitable for a given task.
  • describe the fundamental theory behind the methods.
  • apply the method to example problems with few data.
  • undertake an experimental assessment of learning methods and report the results.
Subject overview

    Meddeles ved kursets start.

This course uses e-learn (blackboard).

Prerequisites for participating in the exam

Assessment and marking:
a) Mandatory assignments, pass/fail, internal evaluation by the teacher.
The mandatory assignments include programming work. The assignments must be passed before the written exam can be attended.
b) 3 hours written exam, Danish 7 mark scale, external examiner.
Calculators may be used but the laptop may not.

The re-exam takes place according to rules decided by the Study Board. It consists of an oral exam with external censor.

Expected working hours
The teaching method is based on three phase model.

Forelæsninger: 28 timer
Eksaminatorietimer: 8 timer
Educational activities

This course is taught in Danish or English, depending on the lecturer. However, if international students participate, the teaching language will always be English.

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.