252-0535-00L Advanced Machine Learning
|Semester||Autumn Semester 2018|
|Lecturers||J. M. Buhmann|
|Periodicity||yearly recurring course|
|Language of instruction||English|
|Performance assessment information (valid until the course unit is held again)|
|Performance assessment as a semester course|
|ECTS credits||8 credits|
|Examiners||J. M. Buhmann|
|Language of examination||English|
|Repetition||The performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.|
|Mode of examination||written 180 minutes|
|Additional information on mode of examination||70% session examination, 30% project; the final grade will be calculated as weighted average of both these elements. As a compulsory continuous performance assessment task, the project must be passed on its own and has a bonus/penalty function.|
The practical project are an integral part (60 hours of work, 2 credits) of the course. Participation is mandatory.
Failing the project results in a failing grade for the overall examination of Advanced Machine Learning (252-0535-00L).
Students who do not pass the project are required to de-register from the exam and will otherwise be treated as a no show.
|Written aids||Two A4-pages (i.e. one A4-sheet of paper), either handwritten or 11 point minimum font size.|
|This information can be updated until the beginning of the semester; information on the examination timetable is binding.|