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Course syllabus - Machine Learning Concepts

Scope

7.5 credits

Course code

DVA262

Valid from

Autumn semester 2026

Education level

First cycle

Progressive Specialisation

G1F (First cycle, has less than 60 credits in first-cycle course/s as entry requirements)

Main area(s)

Computer Science

Organisation

Department of Computer Science & Engineering

Ratified

2022-01-24

Revised

2025-11-03

Literature lists

Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.

Objectives

The purpose of the course is to provide the participants with basic knowledge and conception of supervised and unsupervised machine learning and how they can be applied for classification and regression.

Learning outcomes

After completing the course, the student should be able to:

  1. describe the fundamental needs, challenges, and limitations of machine learning,
  2. describe and understand the basic principles of supervised learning for classification,
  3. describe and understand the basic principles of supervised learning for regression and
  4. describe and understand the basic principles of unsupervised learning.

Course content

  • Fundamentals of Machine Learning.
  • Mathematics for Machine Learning.
  • Supervised Machine Learning for Classification: kNN, DT, Linear Models.
  • Supervised Machine Learning for Regression: Linear Regression.
  • Unsupervised Machine Learning: K-Means, Fuzzy c-Means.

Specific requirements

7,5 credits Object Oriented Programming on level G1F.

Examination

Laboratory work (LAB1), k-NN, 1 credit, examines the learning outcome 2, marks Fail (U) or Pass (G).
Laboratory work (LAB2), Decision Tree, 1 credit, examines the learning outcome 2, marks Fail (U) or Pass (G).
Laboratory work (LAB3), Logistic Regression, 1 credit, examines the learning outcome 2, marks Fail (U) or Pass (G).
Laboratory work (LAB4), Linear Regression, 1 credit, examines the learning outcome 3, marks Fail (U) or Pass (G).
Laboratory work (LAB5), Clustering, 1 credit, examines the learning outcome 4, marks Fail (U) or Pass (G).
Examination (TEN1), Written examination, 2,5 credits, examines the learning outcomes 1-4, marks Fail (U), 3, 4 or 5.

A student who has a certificate from MDU regarding disability study support, can request adaptions for the examination. It is the examiner who takes decisions on any adaptions, based on the certificate and other conditions.

Grade

Grading scale: 5, 4, 3