DE

Block

Advanced Machine Learning [T-WIWI-109921]

Type
Written examination
Credits
4.5
Recurrence
Each summer term
Version
1

Responsible

Organisation

  • KIT-Fakultät für Wirtschaftswissenschaften

Part of

Events

Course Number Name SWS Type
SS20 2540535Advanced Machine Learning 2 lecture (V)
SS24 2540535Advanced Machine Learning 2 lecture (V)
SS21 2540535Advanced Machine Learning 2 lecture (V)
SS23 2540535Advanced Machine Learning 2 lecture (V)
SS22 2540535Advanced Machine Learning 2 lecture (V)
SS21 2540536Exercise Advanced Machine Learning 1 exercise (Ü)
SS23 2540536Exercise Advanced Machine Learning 1 exercise (Ü)
SS20 2540536Exercise Advanced Machine Learning 1 exercise (Ü)
SS24 2540536Exercise Advanced Machine Learning 1 exercise (Ü)
SS22 2540536Exercise Advanced Machine Learning 1 exercise (Ü)

Exams

Course Number Name Appointments
SS22 7900308 Advanced Machine Learning (Nachklausur SS 2021)

14.04.2022 - 11:00

SS22 7900308 Advanced Machine Learning (Nachklausur SoSe 2023)

22.03.2024 - 11:00

SS22 7900308 Advanced Machine Learning

28.07.2021 - 08:00

SS22 7900308 Advanced Machine Learning (Nachklausur 2020)

07.04.2021 - 04:00

SS22 7900308 Advanced Machine Learning

02.08.2023 - 08:00

SS22 7900308 Advanced Machine Learning

31.07.2024 - 11:00

SS22 7900308 Advanced Machine Learning

29.07.2020 - 08:00

SS22 7900308 Advanced Machine Learning

03.08.2022 - 08:00

SS22 7900308 Advanced Machine Learning (Nachklausur SS 2022)

13.04.2023 - 10:00

SS22 7900308 Advanced Machine Learning

29.09.2022 - 10:00

Competence Certificate

Written examination (60 minutes) according to §4(2), 1 SPO. The exam is considered passed if at least 50 out of a maximum of 100 possible points are achieved. The grades are graded in five steps (best grade 1.0 from 95 points). Details of the grade formation and scale will be announced in the course.
A bonus can be acquired through successful participation in the practice. If the grade of the written examination is between 4.0 and 1.3, the bonus improves the grade by one grade level (0.3 or 0.4). The exact criteria for awarding a bonus will be announced at the beginning of the course.

Prerequisites

None