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Blekinge Institute of Technology
Department of Computer Science
Revision: 3
Reg.no: BTH-4.1.14-0269-2026
Course syllabus
Artificial Intelligence
Artificial Intelligence
6 credits (6 högskolepoäng)
Course code: DV1696
Main field of study: Computer Science
Disciplinary domain: Technology
Education level: First-cycle
Specialization: G1N - First cycle, has only upper-secondary level entry requirements
Language of instruction: English
Applies from: 2027-01-18
Approved: 2026-04-14
1. Descision
This course is established by Dean 2023-05-03. The course syllabus is approved by Head of Department of Computer Science 2026-04-14 and applies from 2027-01-18.
2. Entry requirements
3. Objective and content
3.1 Objective
The aim of the course is to introduce students to artificial intelligence (AI) and how AI relates to human intelligence. The course provides an overview of the main techniques used in AI, as well as its potential effects on future societies and individuals. Ethical and safety aspects of AI are central to the course.
3.2 Content
The course includes an overview of central methods and techniques in AI, such as neural networks and statistical methods. Although different subfields of AI are presented, the main focus of the course is on how AI can be used for decision support using algorithms from the subfield of machine learning.
4. Learning outcomes
The following learning outcomes are examined in the course:
4.1. Knowledge and understanding
On completion of the course, the student will be able to:
- reason about similarities and differences between human intelligence and AI
- explain machine learning, including its most common learning paradigms and algorithms
4.2. Competence and skills
On completion of the course, the student will be able to:
- use simple AI models to solve concrete problems
4.3. Judgement and approach
On completion of the course, the student will be able to:
- critically evaluate the opportunities and risks of AI from societal, ethical, and technical perspectives
5. Learning activities
The course is offered as a distance course and includes the following learning activities: lectures, assignments, and discussion seminars related to the assignments. The course uses BTH’s learning platform to distribute course materials (e.g., assignments) and to collect submissions. Additional software tools may also be used.
6. Assessment and grading
Modes of examinations of the course
| Code | Module | Credit | Grade |
| 2410 | Seminar I | 1 credits | GU |
| 2420 | Seminar II | 2 credits | GU |
| 2430 | Seminar III | 3 credits | GU |
The course will be graded G Pass, UX Failed result, a little more work required, U Fail.
The examiner may carry out oral follow-up of written examinations.
The information before the start of the course states the assessment criteria and make explicit in which modes of examination that the learning outcomes are assessed.
An examiner can, after consulting the Disability Advisor at BTH, decide on a customized examination form for a student with a long-term disability to be provided with an examination equivalent to one given to a student who is not disabled.
7. Course evaluation
The course evaluation should be carried out in line with BTH:s course evaluation template and process.
8. Restrictions regarding degree
The course can form part of a degree but not together with another course the content of which completely or partly corresponds with the contents of this course.
9. Course literature and other materials of instruction
Course book:
Life 3.0: Being Human in the Age of Artificial Intelligence
Author: Max Tegmark
Publisher: Volante, 2018
ISBN: 9789188659675
Reference Literature (not required):
Titel: Artificial Intelligence: A Modern Approach (4th Edition)
Authors: Stuart Russell & Peter Norvig
Publisher: Pearson, 2021
ISBN: 978-1292401133