IN5490 – Advanced Topics in Artificial Intelligence for Intelligent Systems

Schedule, syllabus and examination date

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Course content

The course goes in depth on selected topics and methods within artificial intelligence (AI), machine learning (ML) and their applications. Examples include computational intelligence algorithms in search, optimization and classification, which to a large extent consist of bio-inspired mechanisms. Examples of relevant applications include robotics, music, health and medicine. The course syllabus will continuously be updated with methods from state-of-the-art research. The content is based on presentations from ROBIN group staff, the participants and invited guests, and will vary depending on who is involved.

Learning outcome

After taking the course, you will:

  • have insight into the new and promising methods (within evolutionary computation, neural networks, swarm intelligence) used in artificial intelligence (AI) and machine learning (ML)
  • have knowledge about how to apply AI methods to different kinds of applications
  • be able to search for literature outlining state-of-the-art within a specific research field.
  • be able to critically assess scientific papers and be familiar with the structure of a scientific paper
  • be able to design and conduct experiments using AI methods, with emphasis on evaluation
  • have experience in presenting scientific work for others


Students admitted at UiO must apply for courses in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.

Nordic citizens and applicants residing in the Nordic countries may apply to take this course as a single course student.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.

The course is limited to 20 students (IN5490 and IN9495 together). If the number of enrolled students is higher than the limit, they will be ranked as follows:

  1. Phd students who have the course approved in their study plan and who will do research including AI/ML
  2. Master students in the program Informatics: Robotics and Intelligent Systems (I:RIS)
  3. Master students at the Department of Informatics who (will) have the course approved in their study plan and will do master thesis research including AI/ML
  4. Master students at the Faculty of Mathematics and Natural Sciences who (will) have the course approved in their study plan and will do master thesis research including AI/ML
  5. Master students at the Department of Informatics
  6. Others


The teaching will include lectures, discussions and assigment tasks. The teaching will be organized as one or two 1 week workshop sessions (where we will try to take into account possible conflicting lectures in other courses) potentially including lunches. This part of the teaching is joint with IN9495. Additional sessions will be organized during the semester. A part of the course is self-study and tasks to complete before and/or after the weeks with teaching.

80 % attendance of workshop sessions (lectures, discussions etc) is required and the students must be active in discussions and give at least one lecture (about some part of the syllabus). There are mandatory assignments/tasks that must be passed Mandatory assignments and other hand-ins at Department of Informatics 


To pass, the following requirements need to be fulfilled throughout the semester: Students must give at least one presentation, prepare one paper draft and/or get approved compulsory assignments and attend at least 80% of all seminar sessions.

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Explanations and appeals

Resit an examination

Students who have a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.

Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Facts about this course






Every autumn

The semester the course is taught may vary


Every autumn

Same semester as taught

Teaching language