About the course

Artificial Intelligence (AI) can be described as the part of computer science that aims at studying and building intelligent systems (or machines). A system can, for example, be considered intelligent if it thinks or acts like a human in a given situation, or if it is able to perform tasks that normally requires human intelligence. One way to determine whether a system is intelligent is to apply the so-called turing test. The turing test suggests that a machine (system) is intelligent if a person who communicates with it is unable to determine whether it is a machine or a person.

A clear trend in society is that the task we wish to delegate to computer systems is getting more and more advanced; nowadays, it is common that we want computers to be responsible for tasks that normally require intelligent human behavior, such as controling an airplane. AI can therefore be found more and more in the systems we use, for example, in the form of opponents in computer games, decision support systems based on advanced optimization and data mining, and autonomous robots.

In order to understand and develop the current and future computer systems, and to approach advanced problems using computers, it is important to develop a basic understanding of, and ability to apply, concepts and methods found in the AI field. This course aims to support the development of these abilities.

Course content

Syllabus autumn 2024

Earlier syllabuses

Entry requirements and selection

Entry requirements

  1. The equivalent of English 6 in Swedish secondary school.
  2. At least 30 credits in Computer Science, including 15 credits of Object Oriented Programming.

Selection

University credits completed 100%

Course literature

Main literature:

  • Russell, Stuart Jonathan & Norvig, Peter (2010). Artificial intelligence: a modern approach. 3.,[updated] ed. Boston: Pearson Education. ISBN-10: 0136042597
  • Wooldridge, Michael J. (2009). An introduction to multiagent systems. 2nd ed. Chichester, U.K.: John Wiley & Sons. ISBN-10: 0470519460
  • Collection of articles and chapters

Reference literature:

  • Witten, Ian H., Frank, Eibe & Hall, Mark A. (2011). Data mining: practical machine learning tools and techniques. 3. ed. Burlington, MA: Morgan Kaufmann. ISBN-10: 0123748569

Course evaluation

The university provides all students who are participating in, or have completed, a course to express their experiences and views on the course through a course evaluation which is organized at the end of the course. The university will collate the course evaluations and provide information about their results and any actions prompted by them. The results shall be made available to the students. (HF 1:14).

Malmö Day-time 50%

Contact

For more information about the education:

tsstudent@mau.se

This education is provided by

Faculty of Technology and Society

The Faculty of Technology and Society (TS), conducts education and research with a focus on technology and natural sciences, in...

Department of Computer Science and Media Technology

The Department of Computer Science and Media Technology provides research-linked courses and study programmes at first-cycle an...