Search result: Courses in Spring Semester 2020
Computational Biology and Bioinformatics Master More informations at: Link | ||||||||||||||||||||||||
Core Courses Please note that the list of core courses is a closed list. Other courses cannot be added to the core course category in the study plan. Also the assignments of courses to core subcategories cannot be changed. Students need to pass at least one course in each core subcategory. A total of 40 ECTS needs to be acquired in the core course category. | ||||||||||||||||||||||||
Bioinformatics Please note that all Bioinformatics core courses are offered in the autumn semester | ||||||||||||||||||||||||
Biophysics | ||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||
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262-5100-00L | Protein Biophysics (University of Zurich) No enrollment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: BCH304 Mind the enrolment deadlines at UZH: Link | W | 6 credits | 3V + 1U | ||||||||||||||||||||
262-5100-00 V | Protein Biophysics (University of Zurich) **Course at University of Zurich** | 3 hrs | University lecturers | |||||||||||||||||||||
262-5100-00 U | Protein Biophysics (University of Zurich) **Course at University of Zurich** | 1 hrs | University lecturers | |||||||||||||||||||||
151-0980-00L | Biofluiddynamics | W | 4 credits | 2V + 1U | ||||||||||||||||||||
151-0980-00 V | Biofluiddynamics | 2 hrs |
| D. Obrist, P. Jenny | ||||||||||||||||||||
151-0980-00 U | Biofluiddynamics | 1 hrs |
| D. Obrist | ||||||||||||||||||||
Biosystems | ||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||
636-0016-00L | Computational Systems Biology: Stochastic Approaches | W | 4 credits | 3G | ||||||||||||||||||||
636-0016-00 G | Computational Systems Biology: Stochastic Approaches This lecture will be recorded. | 3 hrs |
| M. H. Khammash, A. Gupta | ||||||||||||||||||||
636-0111-00L | Synthetic Biology I Attention: This course was offered in previous semesters with the number: 636-0002-00L "Synthetic Biology I". Students that already passed course 636-0002-00L cannot receive credits for course 636-0111-00L. | W | 4 credits | 3G | ||||||||||||||||||||
636-0111-00 G | Synthetic Biology I ATTENTION: the lecture starts at exactly 08.00 am. The lecture will be held either in Zurich or Basel and will be transmitted via videoconference to the second location. Lecture will be streamed and recorded. | 3 hrs |
| S. Panke, J. Stelling | ||||||||||||||||||||
Data Science | ||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||
551-0364-00L | Functional Genomics Information for UZH students: Enrolment to this course unit only possible at ETH. No enrolment to module BIO 254 at UZH. Please mind the ETH enrolment deadlines for UZH students: Link | W | 3 credits | 2V | ||||||||||||||||||||
551-0364-00 V | Functional Genomics **together with University of Zurich** More information at: Link | 2 hrs |
| C. von Mering, C. Beyer, B. Bodenmiller, M. Gstaiger, H. Rehrauer, R. Schlapbach, K. Shimizu, N. Zamboni, further lecturers | ||||||||||||||||||||
636-0702-00L | Statistical Models in Computational Biology | W | 6 credits | 2V + 1U + 2A | ||||||||||||||||||||
636-0702-00 V | Statistical Models in Computational Biology The lecture will be held either in Zurich or Basel and will be transmitted via videoconference to the second location. Lecture will be streamed and recorded | 2 hrs |
| N. Beerenwinkel | ||||||||||||||||||||
636-0702-00 U | Statistical Models in Computational Biology The tutorial will be held either in Zurich or Basel and will be transmitted via videoconference to the second location. | 1 hrs |
| N. Beerenwinkel | ||||||||||||||||||||
636-0702-00 A | Statistical Models in Computational Biology Project work, no fixed presence required. | 2 hrs | N. Beerenwinkel | |||||||||||||||||||||
636-0019-00L | Data Mining II Prerequisites: Basic understanding of mathematics, as taught in basic mathematics courses at the Bachelor`s level. Ideally, students will have attended Data Mining I before taking this class. | W | 6 credits | 3G + 2A | ||||||||||||||||||||
636-0019-00 G | Data Mining II The lecture will be held each Wednesday either in Zurich or Basel and will be transmitted via videoconference to the second location. Lecture: Wednesday 14-16h Tutorial: 16-17h ***ATTENTION: Starting with the lecture on March 11, the Data Mining II lectures will be broadcasted using a Zoom videoconference. Further information and URL for video is available on the Moodle course website.*** | 3 hrs |
| K. M. Borgwardt | ||||||||||||||||||||
636-0019-00 A | Data Mining II Project Work (compulsory continuous performance assessment), no fixed presence required. | 2 hrs | K. M. Borgwardt | |||||||||||||||||||||
262-6190-00L | Machine Learning | W | 8 credits | 4G | ||||||||||||||||||||
262-6190-00 G | Machine Learning (University of Basel) **Course at University of Basel** Link | 4 hrs | external organisers | |||||||||||||||||||||
252-0220-00L | Introduction to Machine Learning Limited number of participants. Preference is given to students in programmes in which the course is being offered. All other students will be waitlisted. Please do not contact Prof. Krause for any questions in this regard. If necessary, please contact Link | W | 8 credits | 4V + 2U + 1A | ||||||||||||||||||||
252-0220-00 V | Introduction to Machine Learning FS20 CORONA: Keine Aufzeichnung / 17.03.20 rb | 4 hrs |
| A. Krause | ||||||||||||||||||||
252-0220-00 U | Introduction to Machine Learning | 2 hrs |
| A. Krause | ||||||||||||||||||||
252-0220-00 A | Introduction to Machine Learning No presence required. | 1 hrs | A. Krause | |||||||||||||||||||||
636-0101-00L | Systems Genomics | W | 4 credits | 3G | ||||||||||||||||||||
636-0101-00 G | Systems Genomics The lecture is being recorded. Lecture: Wednesday 11-13 Tutorial: Wednesday 17-18 | 3 hrs |
| N. Beerenwinkel, C. Beisel, S. Reddy | ||||||||||||||||||||
Seminar Compulsory seminar. | ||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||
636-0704-00L | Computational Biology and Bioinformatics Seminar | O | 2 credits | 2S | ||||||||||||||||||||
636-0704-00 S | Computational Biology and Bioinformatics Seminar ***ATTENTION: Starting with the lecture on March19, the CBB Seminar will be broadcasted using a Zoom videoconference. The lecturer will inform the students about the URL to participate in the online course*** | 2 hrs |
| J. Stelling, D. Iber, M. H. Khammash, J. Payne, T. Stadler, C. Uhler | ||||||||||||||||||||
Advanced Courses A total of 30 ECTS needs to be acquired in the Advanced Courses category. Thereof 18 ECTS in the Theory and 12 ECTS in the Biology category. Note that some of the lectures are being recorded: Link | ||||||||||||||||||||||||
Theory At least 18 ECTS need to be acquired in this category. | ||||||||||||||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||
252-0063-00L | Data Modelling and Databases | W | 7 credits | 4V + 2U | ||||||||||||||||||||
252-0063-00 V | Data Modelling and Databases | 4 hrs |
| C. Zhang | ||||||||||||||||||||
252-0063-00 U | Data Modelling and Databases Groups are selected in myStudies. | 2 hrs |
| C. Zhang | ||||||||||||||||||||
401-0674-00L | Numerical Methods for Partial Differential Equations Not meant for BSc/MSc students of mathematics. | W | 10 credits | 2G + 2U + 2P + 4A | ||||||||||||||||||||
401-0674-00 G | Numerical Methods for Partial Differential Equations This course is designed in a flipped classroom format based on video tutorials and supplemented by a weekly question-and-answer session, for which attendance is highly recommended. | 2 hrs |
| R. Hiptmair | ||||||||||||||||||||
401-0674-00 U | Numerical Methods for Partial Differential Equations Groups are selected in myStudies. | 2 hrs |
| R. Hiptmair | ||||||||||||||||||||
401-0674-00 P | Numerical Methods for Partial Differential Equations Homework C++ coding projects for the course "Numerical Methods for Partial Differential Equations" | 2 hrs | R. Hiptmair | |||||||||||||||||||||
401-0674-00 A | Numerical Methods for Partial Differential Equations Video guided self-study or group-study for the course "Numerical Methods for Partial Differential Equations" | 4 hrs | R. Hiptmair | |||||||||||||||||||||
401-3052-05L | Graph Theory | W | 5 credits | 2V + 1U | ||||||||||||||||||||
401-3052-05 V | Graph Theory | 28s hrs |
| B. Sudakov | ||||||||||||||||||||
401-3052-05 U | Graph Theory | 7s hrs |
| B. Sudakov | ||||||||||||||||||||
227-1034-00L | Computational Vision (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI402 Mind the enrolment deadlines at UZH: Link | W | 6 credits | 2V + 1U | ||||||||||||||||||||
227-1034-00 V | Computational Vision (University of Zurich) **Course at University of Zurich** | 2 hrs |
| D. Kiper | ||||||||||||||||||||
227-1034-00 U | Computational Vision (University of Zurich) **Course at University of Zurich** Exercise dates by arrangement. | 1 hrs | D. Kiper | |||||||||||||||||||||
227-0558-00L | Principles of Distributed Computing | W | 7 credits | 2V + 2U + 2A | ||||||||||||||||||||
227-0558-00 V | Principles of Distributed Computing | 2 hrs |
| R. Wattenhofer, M. Ghaffari | ||||||||||||||||||||
227-0558-00 U | Principles of Distributed Computing In Gruppen | 2 hrs |
| R. Wattenhofer, M. Ghaffari | ||||||||||||||||||||
227-0558-00 A | Principles of Distributed Computing No presence required. Creative task outside the regular weekly exercises. | 2 hrs | R. Wattenhofer, M. Ghaffari | |||||||||||||||||||||
401-3632-00L | Computational Statistics | W | 8 credits | 3V + 1U | ||||||||||||||||||||
401-3632-00 V | Computational Statistics | 3 hrs |
| M. H. Maathuis | ||||||||||||||||||||
401-3632-00 U | Computational Statistics A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG G 5. | 1 hrs |
| M. H. Maathuis | ||||||||||||||||||||
101-0178-01L | Uncertainty Quantification in Engineering | W | 3 credits | 2G | ||||||||||||||||||||
101-0178-01 G | Uncertainty Quantification in Engineering | 2 hrs |
| S. Marelli | ||||||||||||||||||||
252-0526-00L | Statistical Learning Theory | W | 7 credits | 3V + 2U + 1A | ||||||||||||||||||||
252-0526-00 V | Statistical Learning Theory | 3 hrs |
| J. M. Buhmann, C. Cotrini Jimenez | ||||||||||||||||||||
252-0526-00 U | Statistical Learning Theory | 2 hrs |
| J. M. Buhmann, C. Cotrini Jimenez | ||||||||||||||||||||
252-0526-00 A | Statistical Learning Theory | 1 hrs | J. M. Buhmann, C. Cotrini Jimenez | |||||||||||||||||||||
227-0216-00L | Control Systems II | W | 6 credits | 4G | ||||||||||||||||||||
227-0216-00 G | Control Systems II | 4 hrs |
| R. Smith |
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