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Master's Degree in Artificial Intelligence.

Detailed information about the ideal recommended study plan, etc. is available here.

Semester Schedule for Winter Term 2023/24

To help you get off to a good start, we have put together the schedule for the Winter Semester. This schedule is only a recommendation and can be adjusted to your personal schedule. Please find live streams to Vienna/Bregenz marked with a violet colored upper left corner.



  • Prof. Richard Küng will teach a brand new lecture on “Quantum Computing”, opens an external URL in a new window this Winter Term. This course does not appear yet in our list of Area of Specialiation courses, but we will of course accredit it. You need not use the pre-check form but can directly apply for the accreditation of “Quantum Computing” for “Area of Specialization” at the Examination and Recognition Services.
  • Summer Term 2023: Due to the retirement of Prof. del Re, the courses “Introduction to Autonomous Systems” (VL+UE, 4.5 ECTS) will be replaced by “Introduction to Autonomous Vehicles” (KV, 6 ECTS), taught by Prof. Olaverri-Monreal. The curriculum will be adapted accordingly coming into effect with October 2023. Students following the current study plan can of course accredit the new course (6 ECTS) for the old ones (4.5 ECTS) plus 1.5 ECTS Area of Specialzation, i.e. 6 ECTS for 6 ECTS.

Remote Learning

In order to complete the AI program, students will be required to come to Linz in person at least once in order to officially enroll in the degree program. Some courses will require in-person attendance either in Linz, Bregenz or Vienna.
Students are required to be physically present to take examinations either in Linz, Bregenz or in Vienna. Examinations take place during the course of the entire semester. The curriculum has been designed for students residing in close proximity to Linz, Bregenz or Vienna. 

Many courses in the AI program are offered at the JKU's satellite campus in Vienna and Bregenz as either a live stream or as a video conference.

Course Information

Courses are usually offered only once per year. Starting the study program in a Summer Semester is possible. However, it will require adaption of the course of study compared to the suggested global map of study subjects which is designed for starting in Winter Semester.

Seminar and Practical Work

“Seminar in AI (Master)” (3 ECTS, 3rd semester, Winter terms) and “Practical Work in AI (Master)” (7.5 ECTS, 3rd semester, Winter terms) should prepare the students for their Master’s thesis, although they are allowed to switch their subject again if they want. The courses offered by different institutes will appear as different “group options” for the students in Kusss. Teachers should offer these courses if they want to supervise Master students. The Master’s Thesis itself is formally supervised via the “Master’s Thesis Seminar” (3 ECTS, 4th semester, Summer terms). This course, however, is offered in every term, in particular also in Winter, to allow students to finish their Master’s in 5 semesters, too.

Master Thesis Examination

The curriculum regulates that the Master’s examination consists of two parts: The first part is the student’s successful completion of the mandatory subjects and the elective track according to §§ 4 and 5 of the curriculum. The second part of the Master’s examination is a comprehensive oral exam (1.5 ECTS points).

For this oral exam, the student is supposed to suggest the three members of the examination committee: one committee head (member 1) and two further members (members 2 and 3). This first committee member presides over the thesis defense and may not be the thesis supervisor. The second committee member should examine the subject “Machine Learning and Perception”. The third committee member should examine the chosen elective track. The thesis advisor should be a committee member. While two members may be from the same institute, not all three members should be from the same institute.

The oral exam consists of three parts (20 minutes each): The first part is the presentation and defense of the Master’s thesis (15 minutes presentation plus 5 minutes discussion). This part should be presided over and graded by the head of the committee. The second and third part (20 minutes each) are both dedicated to the examination of the mandatory and the elective track subjects (see previous paragraph) and should be conducted and graded by the respective committee members 2 and 3.

As a basic principle, the Master’s examination may cover all subjects that the student has taken during her/his Master’s degree. Examiners should not narrow down the content of the examination too much beforehand. Additionally, all three examiners are urged to take an active part in all three parts of the examination. Nevertheless, each examiner is formally assigned one part of the examination and responsible for the according grade. The total grade is the rounded average of the three individual grades.

To register for the Master’s examination, students should use this form, opens a file (in the form, the committee head and the first examiner are one and the same person). The first part of the oral exam is already filled in as „Presentation and defense of Master’s thesis“ (in German). Subject two should read “Machine Learning and Perception”, and subject three should name the chosen elective track.


If you have open questions regarding the AI program which are not answered in the information above or in this info file, opens an external URL in a new window, please feel free to contact us:


Contact email of the AI office in Linz: office(at)ai-lab.jku.at

Contact email of the AI office in Vienna: ai-wien(at)jku.at

Contact email of the AI office in Bregenz: ai-bregenz(at)jku.at

Contact email of the Student Union for Computer Science and AI: ai(at)oeh.jku.at

Please also see the webpage of the Student union, opens an external URL in a new window and their Study Guide for Artificial Intelligence, opens an external URL in a new window

Additional information

Feel like studying?

Need an Overview?
Here you will find an overview of general information about the program.