In order to obtain a grade you need to register for the exam by completing the following two steps:
- Register in the "Exam" booking pool on the ILIAS course website. We will use this information to print the correct number of exams and to assigns seats to you. The booking pool will become available 1 month before the exam. Deadline: You need to register in ILIAS at the latest one week before the exam takes place.
- Register in the ALMA portal. All students must also register through ALMA. For some courses or students registration through the ALMA portal might not possible (eg, if Master lectures shall be accredited for Bachelor studies). Please visit this website for more information. Deadline: You need to register at the latest one week before the exam takes place.
The deadlines for canceling the participation of a registered exam can be found here. Cancellations during the registration period are performed via the ALMA portal. Afterwards, students can cancel by sending an email to their examination office. The email must include the title of the course, the name of the lecturer and the date of the exam. Additionally, students must unregister from the exam booking pool in ILIAS. If this is not possible anymore, an email must be sent to our administrative assistant.
In case a student cannot participate in a registered exam due to health reasons, a doctoral attest must be send to us at the latest 3 working days after the exam. Otherwise, the exam will be graded with 5,0.
For compulsory courses (eg, Deep Learning), a make-up exam is offered. The mode of examination will depend on the number of participants. Only students that have participated in the main exam (and failed) as well as students that could not participate in the first exam due to health reasons are allowed to participate in the second exam. In this case, a doctoral attest must be send to our administrative assistant.
You can find the information for which study area a course can be chosen in Campus in the so-called "Strukturbaum". After opening the course of interest, scroll down. As an example, consider the lecture Self-Driving Cars. For ML Master students, this course can be accredited either in "Diverse Topics in Machine Learning" or "General Computer Science". For CS Master students, this course can be accredited either in "INFO-PRAK", "INFO-TECH", "INFO-INFO" or "INFO-APPL".