Search result: Courses in Spring Semester 2021
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 course will be held online only via Zoom throughout the complete semester. The lecturers will communicate the exact lesson times of ONLINE courses. | 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. If the situation allows, this course will take place in classroom after the Easter break. | 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 Starts at 12:15. This course will be held online only via Zoom throughout the complete semester. The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| N. Beerenwinkel | ||||||||||||||
636-0702-00 U | Statistical Models in Computational Biology Starts at 14:15. The tutorial will be held online only via Zoom throughout the complete semester. The lecturers will communicate the exact lesson times of ONLINE courses. | 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 ONLINE only until the end of the semester. ATTENTION: Lecture starts Wednesday, March 3 (no lecture and tutorial in first week) Lecture: Wednesday 14-16h Tutorial: 16-17h The lecturers will communicate the exact lesson times of ONLINE courses. | 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 Findet im ETA F 5 mit Videoübertragung ins ETF E 1 statt | 4 hrs |
| A. Krause, F. Yang | ||||||||||||||
252-0220-00 U | Introduction to Machine Learning Q&A session Wed 16-17 | 2 hrs |
| A. Krause, F. Yang | ||||||||||||||
252-0220-00 A | Introduction to Machine Learning No presence required. | 1 hrs | A. Krause, F. Yang | |||||||||||||||
636-0101-00L | Systems Genomics | W | 4 credits | 3G | ||||||||||||||
636-0101-00 G | Systems Genomics This course will be held online only via Zoom throughout the complete semester. Lecture: Wednesday 11-13 Tutorial: Wednesday 13-14 The lecturers will communicate the exact lesson times of ONLINE courses. | 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: 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 | ||||||||||||||
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 | ||||||||||||||
227-0558-00L | 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 Vorlesung im HG F 1 mit Videoübertragung ins HG F 3. | 3 hrs |
| M. Mächler | ||||||||||||||
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. Mächler | ||||||||||||||
101-0178-01L | Uncertainty Quantification in Engineering | W | 3 credits | 2G | ||||||||||||||
101-0178-01 G | Uncertainty Quantification in Engineering | 2 hrs |
| S. Marelli, B. Sudret | ||||||||||||||
252-0526-00L | Statistical Learning Theory | W | 8 credits | 3V + 2U + 2A | ||||||||||||||
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 | 2 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 | ||||||||||||||
151-0566-00L | Recursive Estimation | W | 4 credits | 2V + 1U | ||||||||||||||
151-0566-00 V | Recursive Estimation The lecture starts in the second week of the Semester. | 2 hrs |
| R. D'Andrea | ||||||||||||||
151-0566-00 U | Recursive Estimation The exercise starts in the second week of the Semester. | 1 hrs |
| R. D'Andrea |
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