Table of contents

The course is connected to the following study programs

Learning outcomes

Upon completion of this course, students will:

  • Have gained a basic understanding of what artificial intelligence and machine learning are.
  • Have acquired a fundamental understanding of how the main types and methods of machine learning work.
  • Have knowledge of the problems that AI can solve.
  • Have developed a simple AI application using available tools, without the need for programming skills.

Contents

Artificial intelligence (AI) is a technology that already impacts our daily lives and is rapidly evolving. Therefore, it is important to understand what AI is and how it works, regardless of the field of study.

This course provides a simple introduction to AI, focusing on machine learning, analytical AI, and generative AI. We explore what AI can and cannot do, and how it is used to solve various problems.

You will also reflect on AI in your own field and develop a simple AI application through a project, without the need for programming skills.

Teaching and learning methods

The course is fully digital, with online sessions and self-study. The expected workload is 67.5 hours.

Examinations

Portfolio assessment. Graded pass/fail. More information about the portfolio will be given in Canvas. There will not be arranged a postponed exam for the portfolio.

Student evaluation

A digital evaluation will be organised in accordance with the quality system for education, chapter 4.1.

Reduction of Credits

This course’s contents overlap with the following courses. A reduction of credits will occur if one of these courses is taken in addition:

Course Reduction of Credits
IKT115 – Introduction to Artificial Intelligence Technology. 2.5
IKT116N – Introduction to Artificial Intelligence. 2.5
Last updated from FS (Felles studentsystem) Oct. 15, 2026 6:32:18 PM