Search result: Courses in Spring Semester 2021

Computational Biology and Bioinformatics Master Information
More informations at: https://www.cbb.ethz.ch
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
NumberTitleTypeECTSHoursLecturers
262-5100-00LProtein 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:
https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html
W6 credits3V + 1U
262-5100-00 VProtein Biophysics (University of Zurich)
**Course at University of Zurich**
3 hrsUniversity lecturers
262-5100-00 UProtein Biophysics (University of Zurich)
**Course at University of Zurich**
1 hrsUniversity lecturers
151-0980-00LBiofluiddynamicsW4 credits2V + 1U
151-0980-00 VBiofluiddynamics2 hrs
Fri10-12HG E 1.2 »
D. Obrist, P. Jenny
151-0980-00 UBiofluiddynamics1 hrs
Fri12-13HG E 1.2 »
D. Obrist
Biosystems
NumberTitleTypeECTSHoursLecturers
636-0016-00LComputational Systems Biology: Stochastic Approaches Information W4 credits3G
636-0016-00 GComputational 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
Mon12-15ON LI NE »
M. H. Khammash, A. Gupta
636-0111-00LSynthetic 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.
W4 credits3G
636-0111-00 GSynthetic 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
Wed08-11BSA E 46 »
08-11HCI J 3 »
S. Panke, J. Stelling
Data Science
NumberTitleTypeECTSHoursLecturers
551-0364-00LFunctional 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
W3 credits2V
551-0364-00 VFunctional Genomics
**together with University of Zurich**
More information at: Link
2 hrs
Mon16-18ML H 41.1 »
C. von Mering, C. Beyer, B. Bodenmiller, M. Gstaiger, H. Rehrauer, R. Schlapbach, K. Shimizu, N. Zamboni, further lecturers
636-0702-00LStatistical Models in Computational BiologyW6 credits2V + 1U + 2A
636-0702-00 VStatistical 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
Thu12-14ON LI NE »
N. Beerenwinkel
636-0702-00 UStatistical 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
Thu14-15ON LI NE »
N. Beerenwinkel
636-0702-00 AStatistical Models in Computational Biology
Project work, no fixed presence required.
2 hrsN. Beerenwinkel
636-0019-00LData 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.
W6 credits3G + 2A
636-0019-00 GData 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
Wed14-17ON LI NE »
K. M. Borgwardt
636-0019-00 AData Mining II
Project Work (compulsory continuous performance assessment), no fixed presence required.
2 hrsK. M. Borgwardt
262-6190-00LMachine LearningW8 credits4G
262-6190-00 GMachine Learning (University of Basel)
4 hrsexternal organisers
252-0220-00LIntroduction to Machine Learning Information Restricted registration - show details
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 is this regard. If necessary, please contact studiensekretariat@inf.ethz.ch
W8 credits4V + 2U + 1A
252-0220-00 VIntroduction to Machine Learning
Findet im ETA F 5 mit Videoübertragung ins ETF E 1 statt
4 hrs
Tue14-16ETA F 5 »
14-16ETF E 1 »
Wed14-16ETA F 5 »
14-16ETF E 1 »
A. Krause, F. Yang
252-0220-00 UIntroduction to Machine Learning
Q&A session Wed 16-17
2 hrs
Fri14-16ML D 28 »
A. Krause, F. Yang
252-0220-00 AIntroduction to Machine Learning
No presence required.
1 hrsA. Krause, F. Yang
636-0101-00LSystems GenomicsW4 credits3G
636-0101-00 GSystems 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
Wed11-14ON LI NE »
N. Beerenwinkel, C. Beisel, S. Reddy
Seminar
Compulsory seminar.
NumberTitleTypeECTSHoursLecturers
636-0704-00LComputational Biology and Bioinformatics SeminarO2 credits2S
636-0704-00 SComputational 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
Thu16-18CHN D 48 »
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: https://video.ethz.ch/lectures.html
Theory
At least 18 ECTS need to be acquired in this category.
NumberTitleTypeECTSHoursLecturers
252-0063-00LData Modelling and Databases Information W7 credits4V + 2U
252-0063-00 VData Modelling and Databases4 hrs
Wed14-16ML D 28 »
Fri08-10ML D 28 »
C. Zhang
252-0063-00 UData Modelling and Databases
Groups are selected in myStudies.
2 hrs
Thu16-18HG F 5 »
Fri14-16CHN C 14 »
C. Zhang
401-0674-00LNumerical Methods for Partial Differential Equations
Not meant for BSc/MSc students of mathematics.
W10 credits2G + 2U + 2P + 4A
401-0674-00 GNumerical 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
Mon16-18HG F 1 »
R. Hiptmair
401-0674-00 UNumerical Methods for Partial Differential Equations
Groups are selected in myStudies.
2 hrs
Fri10-12ETZ E 8 »
10-12HG D 1.1 »
10-12HG G 3 »
11-13ETZ G 91 »
R. Hiptmair
401-0674-00 PNumerical Methods for Partial Differential Equations
Homework C++ coding projects for the course "Numerical Methods for Partial Differential Equations"
2 hrsR. Hiptmair
401-0674-00 ANumerical Methods for Partial Differential Equations
Video guided self-study or group-study for the course "Numerical Methods for Partial Differential Equations"
4 hrsR. Hiptmair
401-3052-05LGraph Theory Information W5 credits2V + 1U
401-3052-05 VGraph Theory28s hrs
Wed/110-12HG E 5 »
Thu/110-12HG F 3 »
B. Sudakov
401-3052-05 UGraph Theory7s hrs
Thu/116-17CAB G 52 »
16-17CAB G 56 »
16-17HG E 33.5 »
17-18HG E 33.5 »
B. Sudakov
227-0558-00LPrinciples of Distributed Computing Information W7 credits2V + 2U + 2A
227-0558-00 VPrinciples of Distributed Computing2 hrs
Wed08-10CAB G 11 »
R. Wattenhofer, M. Ghaffari
227-0558-00 UPrinciples of Distributed Computing
In Gruppen
2 hrs
Wed14-16LFW C 11 »
16-18HG G 26.1 »
R. Wattenhofer, M. Ghaffari
227-0558-00 APrinciples of Distributed Computing
No presence required.
Creative task outside the regular weekly exercises.
2 hrsR. Wattenhofer, M. Ghaffari
401-3632-00LComputational StatisticsW8 credits3V + 1U
401-3632-00 VComputational Statistics
Vorlesung im HG F 1 mit Videoübertragung ins HG F 3.
3 hrs
Thu14-16HG F 1 »
14-16HG F 3 »
Fri09-10HG F 1 »
09-10HG F 3 »
M. Mächler
401-3632-00 UComputational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG G 5.
1 hrs
Fri10-11HG G 5 »
M. Mächler
101-0178-01LUncertainty Quantification in Engineering Information W3 credits2G
101-0178-01 GUncertainty Quantification in Engineering2 hrs
Thu16-18HPV G 5 »
S. Marelli, B. Sudret
252-0526-00LStatistical Learning Theory Information W8 credits3V + 2U + 2A
252-0526-00 VStatistical Learning Theory3 hrs
Mon14-16HG G 3 »
Tue17-18HG F 5 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 UStatistical Learning Theory2 hrs
Mon16-18HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 AStatistical Learning Theory2 hrsJ. M. Buhmann, C. Cotrini Jimenez
227-0216-00LControl Systems II Information W6 credits4G
227-0216-00 GControl Systems II4 hrs
Wed08-12HG E 1.2 »
R. Smith
151-0566-00LRecursive Estimation Information W4 credits2V + 1U
151-0566-00 VRecursive Estimation
The lecture starts in the second week of the Semester.
2 hrs
Wed14-16HG F 1 »
R. D'Andrea
151-0566-00 URecursive Estimation
The exercise starts in the second week of the Semester.
1 hrs
Wed16-17HG F 1 »
R. D'Andrea
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