Block
Introduction to Machine Learning [T-WIWI-111028]
Type
Written examinationCredits
4.5Recurrence
Each winter termVersion
1Organisation
- KIT-Fakultät für Wirtschaftswissenschaften
Part of
Events
Course Number | Name | SWS | Type |
---|---|---|---|
WS22 2540539 | Introduction to Machine Learning | 2 | lecture (V) |
WS20 2540539 | Introduction to Machine Learning | 2 | lecture (V) |
WS21 2540539 | Introduction to Machine Learning | 2 | lecture (V) |
WS23 2540539 | Introduction to Machine Learning | 2 | lecture (V) |
WS22 2540540 | Übung zu Introduction to Machine Learning | 1 | exercise (Ü) |
WS21 2540540 | Übung zu Introduction to Machine Learning | 1 | exercise (Ü) |
WS20 2540540 | Übung zu Introduction to Machine Learning | 1 | exercise (Ü) |
WS23 2540540 | Übung zu Introduction to Machine Learning | 1 | exercise (Ü) |
Exams
Course Number | Name | Appointments |
---|---|---|
WS22 7900349 | Introduction to Machine Learning | 09.03.2021 - 11:00 |
WS22 7900349 | Introduction to Machine Learning | 08.03.2022 - 08:00 |
WS22 7900349 | Introduction to Machine Learning | 15.03.2023 - 11:00 |
WS22 7900349 | Introduction to Machine Learning | 04.10.2022 - 12:00 |
WS22 7900349 | Introduction to Machine Learning (WS 2023/2024) | 12.03.2024 - 08:00 |
WS22 7900349 | Introduction to Machine Learning | 24.09.2024 - 08:00 |
WS22 7900349 | Introduction to Machine Learning | 26.09.2023 - 12:30 |
WS22 7900349 | Introduction to Machine Learning (Nachklausur WS 2020/2021) | 28.09.2021 - 11:00 |
WS22 7900349 | Introduction to Machine Learning | 14.03.2023 - 08:00 |
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-point-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.