Block
Recommender Systems [T-WIWI-102847]
Type
Written examinationCredits
4.5Recurrence
Each winter termVersion
1Responsible
Organisation
- KIT-Fakultät für Wirtschaftswissenschaften
Part of
- Module Data Science: Advanced CRM | Industrial Engineering and Management (M.Sc.)
- Module Data Science: Intelligent, Adaptive, and Learning Information Services | Industrial Engineering and Management (M.Sc.)
- Module Business & Service Engineering | Industrial Engineering and Management (M.Sc.)
- Module Data Science: Advanced CRM | Economics Engineering (M.Sc.)
- Module Data Science: Intelligent, Adaptive, and Learning Information Services | Economics Engineering (M.Sc.)
- Module Business & Service Engineering | Economics Engineering (M.Sc.)
- Module Data Science: Intelligent, Adaptive, and Learning Information Services | Digital Economics (M.Sc.)
- Module Business & Service Engineering | Digital Economics (M.Sc.)
- Module Data Science: Advanced CRM | Information Systems (M.Sc.)
- Module Data Science: Intelligent, Adaptive, and Learning Information Services | Information Systems (M.Sc.)
- Module Information Systems: Analytical and Interactive Systems | Information Systems (M.Sc.)
- Module Business & Service Engineering | Information Systems (M.Sc.)
- Module Data Science: Advanced CRM | Information Engineering and Management (M.Sc.)
- Module Data Science: Intelligent, Adaptive, and Learning Information Services | Information Engineering and Management (M.Sc.)
- Module Business & Service Engineering | Information Engineering and Management (M.Sc.)
Events
| Course Number | Name | SWS | Type |
|---|---|---|---|
| SS20 2540506 | Recommender Systems | 2 | lecture (V) |
| SS21 2540506 | Recommender Systems | 2 | lecture (V) |
| WS22 2540506 | Recommender Systems | 2 | lecture (V) |
| WS23 2540506 | Recommender Systems | 2 | lecture (V) |
| WS21 2540506 | Recommender Systems | 2 | lecture (V) |
| SS22 2540506 | Recommender Systems | 2 | lecture (V) |
| SS21 2540507 | Exercise Recommender Systems | 1 | exercise (Ü) |
| WS23 2540507 | Exercise Recommender Systems | 1 | exercise (Ü) |
| WS22 2540507 | Exercise Recommender Systems | 1 | exercise (Ü) |
| WS21 2540507 | Exercise Recommender Systems | 1 | exercise (Ü) |
| SS20 2540507 | Exercise Recommender Systems | 1 | exercise (Ü) |
Exams
| Course Number | Name | Appointments |
|---|---|---|
| WS20 7900149 | Recommender Systems (Nachklausur SS 2021) | 14.04.2022 - 09:00 |
| WS20 7900149 | Recommender Systems | 10.03.2023 - 08:00 |
| WS20 7900149 | Recommender Systems | 04.10.2022 - 02:00 |
| WS20 7900149 | Recommender Systems (Hauptklausur WS 2021/2022) | 11.03.2022 - 08:00 |
| WS20 7900149 | Recommender Systems | 26.09.2023 - 10:30 |
| WS20 7900149 | Recommender Systems | 06.08.2021 - 11:00 |
| WS20 7900149 | Recommender Systems | 07.08.2020 - 09:00 |
| WS20 7900149 | Recommender Systems (WS 2023/2024) | 14.03.2024 - 02:00 |
| WS20 7900149 | Recommender Systems | 24.09.2024 - 12:00 |
| WS20 7900149 | Recommender Systems | 07.04.2021 - 04:00 |
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
Recommendation
None