Search result: Courses in Autumn Semester 2020
Computer Science Master | |||||||||||||||||||||||||||
Master Studies (Programme Regulations 2020) | |||||||||||||||||||||||||||
Seminar | |||||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | ||||||||||||||||||||||
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263-2100-00L | Research Topics in Software Engineering Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-2100-00 S | Research Topics in Software Engineering The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| Z. Su, M. Vechev | |||||||||||||||||||||||
263-2926-00L | Deep Learning for Big Code Number of participants limited to 24. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-2926-00 S | Deep Learning for Big Code | 2 hrs |
| V. Raychev | |||||||||||||||||||||||
263-3504-00L | Hardware Acceleration for Data Processing The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-3504-00 S | Hardware Acceleration for Data Processing | 2 hrs |
| G. Alonso, A. Klimovic, C. Zhang | |||||||||||||||||||||||
263-3608-00L | Digitalization and the Rebound Effect The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-3608-00 S | Digitalization and the Rebound Effect A maximum number of 11 students can be admitted to the seminar. The seminar is aimed primarily at D-INFK Master's and Bachelor's students in higher semesters, who will be given priority. Should empty spots remain, second priority will be given to Bachelor's students, third priority to Doctoral students. Should the need in either of the categories arise, a random generator will decide upon participation. | 2 hrs |
| V. C. Coroama | |||||||||||||||||||||||
263-3900-01L | Communication Networks Seminar Number of participants limited to 20. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-3900-01 S | Communication Networks Seminar The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| A. Singla, L. Vanbever | |||||||||||||||||||||||
263-4410-00L | Seminar on Advanced Graph Algorithms and Optimization Number of participants limited to 6! The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-4410-00 S | Seminar on Advanced Graph Algorithms and Optimization | 2 hrs | R. Kyng | ||||||||||||||||||||||||
263-5155-00L | Causal Representation Learning The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
263-5155-00 S | Causal Representation Learning The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| B. Schölkopf | |||||||||||||||||||||||
227-2211-00L | Seminar in Computer Architecture Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | |||||||||||||||||||||||
227-2211-00 S | Seminar in Computer Architecture The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| O. Mutlu, M. H. K. Alser, J. Gómez Luna | |||||||||||||||||||||||
Practical Work | |||||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | ||||||||||||||||||||||
252-0811-00L | Applied Security Laboratory This only applies to Study Regulations 09: In the Master Programme max. 10 credits can be accounted by Labs on top of the Interfocus Courses. Additional Labs will be listed on the Addendum. | W | 8 credits | 7P | |||||||||||||||||||||||
252-0811-00 P | Applied Security Laboratory Will also be offered via Zoom. If more than 20 students register, the lecturer will communicate the distribution of who will attend the course on site and who will attend from home.” | 7 hrs |
| D. Basin | |||||||||||||||||||||||
252-0817-00L | Distributed Systems Laboratory This only applies to Study Regulations 09: In the Master Programme max.10 credits can be accounted by Labs on top of the Interfocus Courses. These Labs will only count towards the Master Programme. Additional Labs will be listed on the Addendum. | W | 10 credits | 9P | |||||||||||||||||||||||
252-0817-00 P | Distributed Systems Laboratory Lab projects are typically carried out in groups of two or three students. | 9 hrs | by appt. | G. Alonso, T. Hoefler, A. Klimovic, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang | |||||||||||||||||||||||
263-5905-00L | Mixed Reality Laboratory This only applies to Study Regulations 09: In the Master Programme max. 10 credits can be accounted by Labs on top of the Interfocus Courses. Additional Labs will be listed on the Addendum. | W | 10 credits | 9P | |||||||||||||||||||||||
263-5905-00 P | Mixed Reality Laboratory | 9 hrs |
| F. Bogo, M. R. Oswald | |||||||||||||||||||||||
263-0650-00L | Practical Work | W | 8 credits | 17A | |||||||||||||||||||||||
263-0650-00 A | Praktische Arbeit | 240s hrs | by appt. | Supervisors | |||||||||||||||||||||||
Minors | |||||||||||||||||||||||||||
Minor in Computer Graphics | |||||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | ||||||||||||||||||||||
252-0543-01L | Computer Graphics | W | 8 credits | 3V + 2U + 2A | |||||||||||||||||||||||
252-0543-01 V | Computer Graphics The lecturers will communicate the exact lesson times of ONLINE courses. | 3 hrs |
| M. Gross, M. Papas | |||||||||||||||||||||||
252-0543-01 U | Computer Graphics The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| M. Gross, M. Papas | |||||||||||||||||||||||
252-0543-01 A | Computer Graphics | 2 hrs | M. Gross, M. Papas | ||||||||||||||||||||||||
252-0546-00L | Physically-Based Simulation in Computer Graphics | W | 5 credits | 2V + 1U + 1A | |||||||||||||||||||||||
252-0546-00 V | Physically-Based Simulation in Computer Graphics The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| V. da Costa de Azevedo, B. Solenthaler | |||||||||||||||||||||||
252-0546-00 U | Physically-Based Simulation in Computer Graphics The lecturers will communicate the exact lesson times of ONLINE courses. | 1 hrs |
| V. da Costa de Azevedo, B. Solenthaler | |||||||||||||||||||||||
252-0546-00 A | Physically-Based Simulation in Computer Graphics | 1 hrs | V. da Costa de Azevedo, B. Solenthaler | ||||||||||||||||||||||||
Minor in Computer Vision | |||||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | ||||||||||||||||||||||
263-3210-00L | Deep Learning | W | 8 credits | 3V + 2U + 2A | |||||||||||||||||||||||
263-3210-00 V | Deep Learning The lecturers will communicate the exact lesson times from «online» courses. | 3 hrs |
| T. Hofmann | |||||||||||||||||||||||
263-3210-00 U | Deep Learning | 2 hrs |
| T. Hofmann | |||||||||||||||||||||||
263-3210-00 A | Deep Learning | 2 hrs | T. Hofmann | ||||||||||||||||||||||||
263-5902-00L | Computer Vision | W | 8 credits | 3V + 1U + 3A | |||||||||||||||||||||||
263-5902-00 V | Computer Vision The lecturers will communicate the exact lesson times of ONLINE courses. | 3 hrs |
| M. Pollefeys, S. Tang, V. Ferrari | |||||||||||||||||||||||
263-5902-00 U | Computer Vision | 1 hrs |
| M. Pollefeys, S. Tang, V. Ferrari | |||||||||||||||||||||||
263-5902-00 A | Computer Vision | 3 hrs | M. Pollefeys, S. Tang, V. Ferrari | ||||||||||||||||||||||||
Minor in Data Management | |||||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | ||||||||||||||||||||||
252-0535-00L | Advanced Machine Learning | W | 10 credits | 3V + 2U + 4A | |||||||||||||||||||||||
252-0535-00 V | Advanced Machine Learning The lectures will mostly be given in a lecture hall with limited attendance (at most 50% of lecture hall capacity). It will be possible to join remotely via zoom with acccess to slides, whiteboard, and speaker camera. Students can interact, e.g. ask questions, physically as well as digitally. The lectures will be recorded via zoom’s recording functionality. | 3 hrs |
| J. M. Buhmann, C. Cotrini Jimenez | |||||||||||||||||||||||
252-0535-00 U | Advanced Machine Learning | 2 hrs |
| J. M. Buhmann, C. Cotrini Jimenez | |||||||||||||||||||||||
252-0535-00 A | Advanced Machine Learning Project Work, no fixed presence required. | 4 hrs | J. M. Buhmann, C. Cotrini Jimenez | ||||||||||||||||||||||||
263-2800-00L | Design of Parallel and High-Performance Computing | W | 9 credits | 3V + 2U + 3A | |||||||||||||||||||||||
263-2800-00 V | Design of Parallel and High-Performance Computing | 3 hrs |
| T. Hoefler, M. Püschel | |||||||||||||||||||||||
263-2800-00 U | Design of Parallel and High-Performance Computing | 2 hrs |
| T. Hoefler, M. Püschel | |||||||||||||||||||||||
263-2800-00 A | Design of Parallel and High-Performance Computing Project Work, no fixed presence required. | 3 hrs | T. Hoefler, M. Püschel | ||||||||||||||||||||||||
263-3010-00L | Big Data | W | 10 credits | 3V + 2U + 4A | |||||||||||||||||||||||
263-3010-00 V | Big Data The lecturers will communicate the exact lesson times of ONLINE courses. | 3 hrs |
| G. Fourny | |||||||||||||||||||||||
263-3010-00 U | Big Data Groups are selected in myStudies. The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| G. Fourny | |||||||||||||||||||||||
263-3010-00 A | Big Data Individual work to get hands-on experience with the technologies covered, no fixed presence required. | 4 hrs | G. Fourny | ||||||||||||||||||||||||
263-3210-00L | Deep Learning | W | 8 credits | 3V + 2U + 2A | |||||||||||||||||||||||
263-3210-00 V | Deep Learning The lecturers will communicate the exact lesson times from «online» courses. | 3 hrs |
| T. Hofmann | |||||||||||||||||||||||
263-3210-00 U | Deep Learning | 2 hrs |
| T. Hofmann | |||||||||||||||||||||||
263-3210-00 A | Deep Learning | 2 hrs | T. Hofmann |
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