252-0535-00L Advanced Machine Learning
|Semester||Autumn Semester 2020|
|Lecturers||J. M. Buhmann, C. Cotrini Jimenez|
|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||10 credits|
|Examiners||J. M. Buhmann, C. Cotrini Jimenez|
|Language of examination||English|
|Repetition||The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.|
|Mode of examination||written 180 minutes|
|Additional information on mode of examination||The practical projects are an integral part of the course (60 hours of work, 2 credits). Participation is mandatory. A failing grade for the practical projects will result in a failing grade for the course.|
For students who obtain a passing grade for the practical projects, the final grade for the course will be calculated as a weighted average of the grade achieved in the written examination (70%) and the grade achieved in the practical projects (30%).
Students who achieve a failing grade in the practical projects have to de-register from the exam. Otherwise, they will not be admitted to the exam and will be treated as no-shows.
The exam might take place at a computer.
|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.|