Module Number ML-4501 |
Module Title Machine Learning Seminar |
Lecture Type(s) Seminar |
---|---|---|
ECTS | 3 | |
Work load - Contact time - Self study |
Workload:
90 h Class time:
30 h / 2 SWS Self study:
60 h |
|
Duration | 1 Semester | |
Frequency | Irregular | |
Language of instruction | English | |
Type of Exam | Presentation and written report |
|
Content | In this module we discuss advanced results and approaches in machine learning theory and application and current research results in the area of machine learning in general. Please refer to the curse catalogue in alma to see which specific courses are offered in a respective semester. |
|
Objectives | Students get to know about advanced results in machine learning theory and applications. They can judge for example whether an algorithm is well designed, both from an algorithmic and statistical point of view. They understand about the fundamental limitations of machine learning. They can reflect current research questions. Students will be able to acquire knowledge about current findings through comprehensive literature search. They will know the importance of current topics in the area of machine learning, and will be aware that there are still many open questions. Students will not only have improved their study and reading skills, but will also have enhanced their capability of working independently. The teaching method in this seminar aims at boosting the students’ confidence (oral presentation), and at enhancing their communication skills and enabling them to accept criticism (discussion session following their presentation. After this module they are well-prepared to write a master thesis in the area of machine learning. |
|
Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Seminar
S
o
2
3.0
tp,
op
30
g
100
|
|
Prerequisite for participation | There are no specific prerequisites. | |
Lecturer / Other | Alle Dozenten | |
Literature | Will be handed out in the course |
|
Last offered | Wintersemester 2022 | |
Planned for | Wintersemester 2024 | |
Assigned Study Areas | INFO-INFO, MEDI-APPL, MEDI-INFO, MEDZ-SEM, ML-CS, ML-DIV |