Semester selection: WiSe 2026/2027 SoSe 2026 WiSe 2025/2026 SoSe 2025 WiSe 2024/2025 Previous...
The individual module components can only be studied in specific combinations.
A total of two graded partial examinations and one coursework assignment must be completed.
The following requirements must be met for each combination:
Path 1
Partial examination 1 – Option A: Portfolio with a written final examination (for the lecture + accompanying exercise combination)
Partial examination 2 – Option A: Presentation with a written paper (for the Application-oriented seminar 1 + Application-oriented seminar 2 combination)
Path 2
Partial examination 1 – Option A: Portfolio with a written final examination (for the combination of lecture + accompanying exercise)
Partial examination 2 – Option B: Report (project)
Path 3
Partial examination 1 – Option B: Portfolio with an oral final examination (for the combination of seminar + accompanying exercise)
Partial examination 2 - Option B: Report (project)
Partial examinations are linked exclusively to the following course types:
Coursework is linked to the following course types and must be completed if the course is selected:
Justification of necessity of two partial module examinations:
Two partial examinations are necessary since the theoretical and mathematical competencies are tested in the written/oral examination and practical and methodological knowledge in the project/second seminar.
| Reference no. | Teaching staff | Topic | Type | Dates | My eKVV |
|---|---|---|---|---|---|
| 392221 | Hammer | Deep Learning Course taught in English | V | Wed 12-14 in H5 [07.04.-18.07.2025] Am 02.07. fällt die Vorlesung aus! |
|
| 392221 | Hammer |
Klausur: Deep Learning - 1. Termin
Registration via the electronic course catalogue (eKVV) by
7/9/25
Course taught in English
|
Kl |
|
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| 392221 | Hammer |
Klausur: Deep Learning - 2. Termin
Registration via the electronic course catalogue (eKVV) by
9/26/25
Course taught in English
|
Kl |
|
| Reference no. | Teaching staff | Topic | Type | Dates | My eKVV |
|---|---|---|---|---|---|
| 392155 | Rhodin, Appolinary, Schröder, Bhattarai | Generative Models for Visual Computing Course taught in English | S | Wed 10-12 in H9 [07.04.-18.07.2025] |
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| Reference no. | Teaching staff | Topic | Type | Dates | My eKVV |
|---|---|---|---|---|---|
| 392222 | Hammer, Kenneweg | Tutorial Deep Learning | Ü | Thu 12-14 in H16 [07.04.-18.07.2025] |
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| 392223 | Hammer, Kenneweg | Additional Tutorial "Deep Learning" | Ü | Wed 14-16 ONLINE [07.04.-18.07.2025] |
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No courses found
No courses found
| Reference no. | Teaching staff | Topic | Type | Dates | My eKVV |
|---|---|---|---|---|---|
| 392109 | Kappel | Journal Club: Foundations of Sustainable Machine Learning Course taught in English | S | Thu 12-14 in CITEC 1.015 [07.04.-18.07.2025] |
|
| 392155 | Rhodin, Appolinary, Schröder, Bhattarai | Generative Models for Visual Computing Course taught in English | S | Wed 10-12 in H9 [07.04.-18.07.2025] |
|
| Reference no. | Teaching staff | Topic | Type | Dates | My eKVV |
|---|---|---|---|---|---|
| 392109 | Kappel | Journal Club: Foundations of Sustainable Machine Learning Course taught in English | S | Thu 12-14 in CITEC 1.015 [07.04.-18.07.2025] |
|
| 392155 | Rhodin, Appolinary, Schröder, Bhattarai | Generative Models for Visual Computing Course taught in English | S | Wed 10-12 in H9 [07.04.-18.07.2025] |
|