EPN-V2

DAVE3625 Introduction to Artificial Intelligence Course description

Course name in Norwegian
Introduksjon til Kunstig Intelligens
Study programme
Bachelor in Applied Computer Technology
Bachelor's Degree Programme in Software Engineering
Bachelor’s Programme in Electrical Engineering
Bachelor's Degree Programme in Mathematical Modelling and Data Science
Bachelor's Degree Programme in Information Technology
Weight
10.0 ECTS
Year of study
2025/2026
Curriculum
FALL 2025
Schedule
Programme description
Course history

Introduction

This course provides a broad introduction to Artificial Intelligence (AI), with methodologies and techniques that can be applied to different application domains. The course will balance theoretical approaches and practical tasks.

Recommended preliminary courses

Basic programming skills (C, Python, Java, or similar programming language)

Required preliminary courses

None

Learning outcomes

On successful completion of the course, the student should have the following learning outcomes defined in terms of knowledge, skills and general competence.

Knowledge

The student:

  • Knows how the field of artificial intelligence developed historically
  • Is familiar with the main artificial intelligence theories and has a practical understanding of the development and use of artificial intelligence
  • Can reflect on the practical, social and ethical implications of the development of artificial intelligence
  • Has an understanding of the current application areas of artificial intelligence

Skills

The student:

  • Has the theoretical and practical skills to build simple artificial intelligence systems
  • Can use a variety of state-of-the-art artificial intelligence techniques in different application domains
  • Can evaluate the technical quality and practical value of various types of artificial intelligence

Competence

The student:

  • Has both theoretical and practical understanding of artificial intelligence methods
  • Is able to solve real-life problems using artificial intelligence methods

Teaching and learning methods

The course consists of lectures and seminars on techniques and methods.

The students will work in groups for the mandatory assignments. Lab sessions supporting the assignments will be provided.

Course requirements

3 compulsory assignments done in groups of 2-4 students must be approved in order to be admitted to the final exam.

Assessment

Individual written examination (4 hours).

The exam result can be appealed.

In the case of a new and postponed exam, another form of exam can also be used or a new assignment with a new deadline is given. If an oral examination is used, this cannot be appealed.

Permitted exam materials and equipment

No support materials are allowed for the written exam.

Grading scale

Grade scale A-F.

Examiners

Two examiners. External examiner is used periodically.