Table of contents

The course is connected to the following study programs

Teaching language

English

Learning outcomes

After completing the course, the student is expected to:

  • understand the methods in system modelling and simulation
  • be able to create and use digital models
  • know the challenges and benefits of using digital models
  • understand the role of languages to describe models
  • be able to compare different models of the same reality

Contents

  • Models, systems, and reality: similarities and differences.
  • Domain modelling: approach and tools.
  • Behavior modelling: notations and architectures.
  • Language modelling: domain-specific languages, frameworks, and tools.
  • Model semantics: correctness, simulations and realizations.

Teaching and learning methods

Lectures, project work, supervision. The workload for the average student is approximately 200 hours.

Examinations

Project report and adjusting oral examination. Graded assessment.

Student evaluation

The person responsible for the course decides, in cooperation with the student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.

Offered as a free-standing course

Yes. Subject to availability or capacity.

Admission Requirement if given as a free-standing course

Admission requirements for the course are the same as for the master’s programme in AI and IoT.
Last updated from FS (Felles studentsystem) Oct. 15, 2026 1:37:16 PM