Detailed information about the ideal recommended study plan, etc. is available here.
The LIT Artificial Intelligence Lab would like to extend an invitation to attend a Welcome Event (featuring a Q&A session) at the beginning of the 2024 Winter Term.
Date: Tuesday, October 1, 2024, beginning at 3:30 PM
Four potential locations:
Please check out the details here.
To help you get off to a good start, we have put together the schedule for the winter and summer term. This schedule is for reference only and can be adjusted to your personal schedule. The livestreams to Vienna/Bregenz are marked in violet in the upper left corner.
Ass.-Prof. Johannes Brandstetter offers a Special Topics in AI course named "Deep Learning: Geometric Techniques" for the first time in winter term 2024/25. It is based on the course "Geometric Deep Learning" taught by Michael Bronstein at the University of Oxford. As this course requires advanced knowledge in deep learning, maths and physics, it is recommended to be taken only after having taken at least one course in deep learning by Prof. Günter Klambauer and during your second or third Master´s semester.
In order to successfully 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 in person. Some courses will require on-site and 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 may take place during the entire semester. The curriculum has been designed for students residing in close proximity to Linz, Bregenz, or Vienna.
Many of the courses in the AI program are offered at the JKU's satellite campus in Vienna and Bregenz, as either as a livestream or as a video conference (please check schedule).
Courses are usually offered only once a year. While you can enroll during the Summer Semester to begin studying AI, starting the program at this time means you may be subject to adjusting your schedule differently as compared to the suggested schedule of courses. We highly recommend starting the program in October.
The “Seminar in AI (Master's degree program)” (3 ECTS credits, 3rd semester, Winter Semester) and “Practical Work in AI (Master's program)” (7.5 ECTS credits, 3rd semester, Winter Semester) have been designed to help students prepare to write the required Master’s degree thesis. Students can, however, switch their subject area again, if they wish to. Different institutes will offer courses in KUSSS which students will consider to be different “group options”. Faculty members will offer these courses when supervising undegraduate students. The Master’s thesis itself is formally supervised via the “Master’s Thesis Seminar” (3 ECTS credits, 4th semester, Summer Semester). This course is, however, offered during each semester, allowing students to complete their Masters’s degree during the Winter Semester as well.
The Master's degree examination is outlined in curriculum and consists of two sections. The first section requires the student to successfully complete all of the required subjects and the elective track in accordance with §§ 4 and 5 of the curriculum. The second section of the Master’s degree examination is a comprehensive oral examination (1.5 ECTS credits).
As part of the oral examination, the student will be asked to put a 3-member examination committee together, consisting of a committee head (member 1) and two additional members (members 2 and 3). This first committee member may not be a thesis supervisor and will preside over the oral defense. The second committee member will conduct an examination in the subject area of “Machine Learning and Perception”. The third committee member will conduct an examination in regard to the selected elective track. The thesis supervisor should also be a member of the committee. Whereas two committee members may be from the same institute, all of the committee members should not be from the same institute.
The oral exam consists of three sections (20 minutes each): The first section requires presenting and defending the Master’s thesis (a 15-minute presentation, plus 5 minutes of Q&A). The head of the committee will preside over this section and provide a grade. The second and third sections (20 minutes each) will focus examining the required and elective track subjects (see the paragraph above); committee members 2 and 3 will conduct and grade this section.
In general, the Master’s examination may cover all of the subjects that the student has taken during the course of the Master’s degree program. Examiners will not narrow the examination content too much beforehand. In addition, all three of the examiners are encouraged to actively take in all three sections of the examination. Nevertheless, each examiner will be formally assigned one section of the examination and is responsible for grading. The overall grade is the rounded average from the three individual grades.
Please use this form, opens a file to sign up for the Master's examination (in the form, the committee head and the first examiner are one and the same person). The first section of the oral examination is already filled out as "Presentation and Defense of Master’s Thesis" (in German). Subject two should read “Machine Learning and Perception”, and subject three should be the selected elective track.
In order to coordinate a date for the Master's examination, please note that all of the professors at the Institute for Machine Learning save the last Tuesday and Wednesday of each month for this purpose.
It is possible to start the program in summer term. Nevertheless, as all courses are only offered once a year and start in winter term, it is difficult to follow the study plan with 30 ECTS per semester. Only in exceptional cases in which a student has the necessary knowledge of introductory courses and plans to later accredit those, a start in summer term is advisable.
Yes, for all lectures (LV) and combined courses (KV), you can still register. Please write an e-mail to the teacher or the institute´s secretary to ask for late registration. For tutorial groups, this might be more difficult as they are quickly fully booked and also require attendance (in person or online) and regular submissions.
It makes sense to first take these introductory courses from the Bachelor´s program. Nevertheless, you can also take other Master courses in parallel.
In general, all lectures in the program are recorded and can be accessed in Moodle. For the tutorial groups, please register for the groups with distance learning option in KUSSS.
Please check the timetable. Streamed courses are color-coded.
You can still register and will be put on a waiting list if the group is already fully booked. If spots free up, you are first in line as well as if new tutorial groups are created. If the registration period is over you can still write an e-mail to the teacher or in case of courses offered from the Institute for Machine Learning to office@ai-lab.jku.at.
Some exams are offered online, others have to be taken in person in the lecture hall in Vienna, Bregenz or Linz. Please register online in KUSSS for one of the options offered.
In Linz you can meet them in the lecture hall. Our distance learning centres in Vienna and Bregenz offer rooms to study together and follow the streams every day of the week (not only at the times of the scheduled streams). Also a discord channel, opens an external URL in a new window was created for this reason.
You find an excel on top of the website that you should fill out and send together with all certificates as well as descriptions of the successfully completed courses to office(at)ai-lab.jku.at
For some courses and only once you have gotten a matriculation number after being officially enrolled in the program, we can grant you access to course materials in moodle. Please write an e-mail to office(at)ai-lab.jku.at in this case.
Here, opens an external URL in a new window you can find more answers to your questions by the Austrian Students´ Union (ÖH).
FAQs, opens an external URL in a new window for international students by the Austrian Students´ Union (ÖH).
If you have any questions or concerns regarding the AI program that have not been addressed above or below, please feel free to contact us by sending an e-mail to::
The AI office in Linz: office(at)ai-lab.jku.at
The AI office in Vienna: ai-wien(at)jku.at
The AI office in Bregenz: ai-bregenz(at)jku.at
The Austrian Student Union for Computer Science and AI: ai(at)oeh.jku.at
Please also see: Austrian Student Union, opens an external URL in a new window and the Study Guide for Artificial Intelligence, opens an external URL in a new window
You are eager to get a job in Austria? You are thinking of starting your own startup, opens an external URL in a new window?
The Austrian Business Agency, opens an external URL in a new window (ABA), the business location agency of the Austrian Ministry of Economy, is eager to help. As a government agency, ABA offers free-of-charge support and information for international students and graduates at Austrian universities. More information here, opens an external URL in a new window.
Need an Overview?
Here you will find an overview of general information about the program.
Johannes Kepler University Linz
Altenberger Straße 69
4040 Linz, Austria
