Search result: Courses in Spring Semester 2018

Computational Biology and Bioinformatics Master Information
More informations at: Link
Master Studies (Programme Regulations 2017)
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
551-0307-01LMolecular and Structural Biology II: From Gene to Protein
D-BIOL students are obliged to take part I and part II as a two-semester course.
W3 credits2V
551-0307-01 VMolecular and Structural Biology II: From Gene to Protein2 hrs
Mon12:45-14:30HCI J 3 »
N. Ban, F. Allain, M. Pilhofer
262-5100-00LProtein Biophysics (University of Zurich) Information
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
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
Biosystems
NumberTitleTypeECTSHoursLecturers
636-0006-00LComputational Systems Biology: Deterministic Approaches Restricted registration - show details W4 credits3G
636-0006-00 GComputational Systems Biology: Deterministic Approaches Special students and auditors need a special permission from the lecturers.
Students are expected to have completed the courses Computational systems biology’ and ‘Spatio-temporal modeling in biology’ (MSc Computational biology and bioinformatics), which provide the foundational knowledge for the course.
3 hrs
Tue13:15-16:00BSB E 4 »
J. Stelling, D. Iber
636-0016-00LComputational Systems Biology: Stochastic Approaches Information W4 credits3G
636-0016-00 GComputational Systems Biology: Stochastic Approaches
No Lecture on Monday, Feb. 19
Regular start of Lecture: Monday, February 26
3 hrs
Mon14:15-17:00BSA E 46 »
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.
3 hrs
Wed07:45-10:30HCI J 3 »
08:15-11:00BSA E 46 »
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**
2 hrs
Mon15:15-17:00ML 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
The lecture will be held either in Zurich or Basel and will be transmitted via videoconference to the second location.
2 hrs
Thu12:15-14:00BSB E 4 »
12:15-14:00HG D 16.2 »
N. Beerenwinkel
636-0702-00 UStatistical 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
Thu14:15-15:00BSB E 4 »
14:15-15:00HG D 16.2 »
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 each Wednesday either in Zurich or Basel and will be transmitted via videoconference to the second location.
Lecture in Basel/Zürich: Wednesday 14-16h, Tutorial 16-17h (BSB E4 Room "Manser" / HG D16.2)
3 hrs
Wed14:15-17:00BSB E 4 »
14:15-17:00HG D 16.2 »
K. M. Borgwardt
636-0019-00 AData Mining II
Project work, no fixed presence required.
2 hrsK. M. Borgwardt
262-6190-00LMachine LearningW8 credits4G
262-6190-00 GMachine Learning (University of Basel)
**Course at University of Basel**
4 hrsexternal organisers
Seminar
Compulsory seminar.
NumberTitleTypeECTSHoursLecturers
636-0704-00LComputational Biology and Bioinformatics SeminarO2 credits2S
636-0704-00 SComputational Biology and Bioinformatics Seminar2 hrs
Thu15:15-17:00CHN D 48 »
J. Stelling, M. Claassen, G. H. Gonnet, D. Iber, 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.
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
Wed13:15-15:00HG F 3 »
Fri08:15-10:00HG F 3 »
G. Alonso, C. Zhang
252-0063-00 UData Modelling and Databases2 hrs
Thu15:15-17:00CAB G 11 »
Fri13:15-15:00CHN C 14 »
G. Alonso, C. Zhang
401-0674-00LNumerical Methods for Partial Differential Equations
Not meant for BSc/MSc students of mathematics.
W8 credits4V + 2U + 1A
401-0674-00 VNumerical Methods for Partial Differential Equations
Additional classes on Tuesday 27 March and 10 April 2018, 17-18 and Wednesday 11 April 2018, 16-18 in HG F 1
No classes on 16 and 17 April 2018
(the weekly exercises take place as usual)
4 hrs
Mon15:15-17:00HG F 1 »
Tue15:15-17:00HG F 1 »
27.03.17:15-18:00HG F 1 »
10.04.17:15-18:00HG F 1 »
11.04.16:15-17:00HG F 1 »
17:15-19:00HG F 1 »
R. Hiptmair
401-0674-00 UNumerical Methods for Partial Differential Equations
Thu 13-15 or Fri 8-10 or Fri 10-12
(Fri 10-12 for Computational Science and Engineering Bachelor)
2 hrs
Thu13:15-15:00ML J 34.1 »
Fri08:15-10:00HG D 5.2 »
10:15-12:00HG D 5.2 »
R. Hiptmair
401-0674-00 ANumerical Methods for Partial Differential Equations
Attendance of lectures and tutorials for 401-0674-00 V Numerical Methods for Partial Differential Equations required. All regulations and requirements for that course apply.
1 hrsR. Hiptmair
401-3052-05LGraph Theory Information W5 credits2V + 1U
401-3052-05 VGraph Theory28s hrs
Wed/110:15-12:00HG E 1.1 »
Thu/110:15-12:00HG E 1.1 »
B. Sudakov
401-3052-05 UGraph Theory7s hrs
Thu/115:15-16:00CAB G 52 »
15:15-16:00CAB G 56 »
15:15-16:00HG D 5.3 »
15:15-16:00HG E 21 »
15:15-16:00ML J 34.1 »
B. Sudakov
227-1034-00LComputational Vision (University of Zurich) Information
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
W6 credits2V + 1U
227-1034-00 VComputational Vision (University of Zurich)
**Course at University of Zurich**
2 hrs
Thu17:15-19:00Y35 F 32 »
D. Kiper, K. A. Martin
227-1034-00 UComputational Vision (University of Zurich)
**Course at University of Zurich**
Exercise dates by arrangement.
1 hrsby appt.D. Kiper, K. A. Martin
252-0220-00LIntroduction to Machine Learning Information
Previously called Learning and Intelligent Systems

Prof. Krause approves that students take distance exams, also if the exam will take place at a later time due to a different time zone of the alternative exam place.
To get Prof. Krause's signature on the distance exam form please send it to Rita Klute, Link.
W8 credits4V + 2U + 1A
252-0220-00 VIntroduction to Machine Learning
Die Vorlesung findet jeweils (Di 13-15 und Mi 13-15) im ML D 28 mit Videoübertragung im ML E 12 statt.
4 hrs
Tue13:15-15:00ML D 28 »
13:15-15:00ML E 12 »
Wed13:15-15:00ML D 28 »
13:15-15:00ML E 12 »
29.05.13:15-15:00HG E 3 »
13:15-15:00HG F 30 »
A. Krause
252-0220-00 UIntroduction to Machine Learning2 hrs
Mon15:15-17:00HG D 1.2 »
Tue15:15-17:00HG D 1.2 »
Wed15:15-17:00CAB G 11 »
Fri13:15-15:00ML D 28 »
A. Krause
252-0220-00 AIntroduction to Machine Learning
No presence required.
1 hrsA. Krause
227-0558-00LPrinciples of Distributed Computing Information W6 credits2V + 2U + 1A
227-0558-00 VPrinciples of Distributed Computing2 hrs
Wed08:15-10:00CAB G 11 »
R. Wattenhofer, M. Ghaffari
227-0558-00 UPrinciples of Distributed Computing
In Gruppen
2 hrs
Wed10:15-12:00CAB G 56 »
13:15-15:00LFW C 11 »
R. Wattenhofer, M. Ghaffari
227-0558-00 APrinciples of Distributed Computing
No presence required.
Creative task outside the regular weekly exercises.
1 hrsR. Wattenhofer, M. Ghaffari
401-3632-00LComputational StatisticsW10 credits3V + 2U
401-3632-00 VComputational Statistics
On 29 March 2018 the course takes place in HG E 3.
3 hrs
Thu13:15-15:00HG F 3 »
Fri09:15-10:00HG G 3 »
29.03.13:15-15:00HG E 3 »
M. H. Maathuis
401-3632-00 UComputational Statistics2 hrs
Fri10:15-12:00HG F 3 »
M. H. Maathuis
101-0178-01LUncertainty Quantification in Engineering Information W3 credits2G
101-0178-01 GUncertainty Quantification in Engineering2 hrs
Thu14:45-16:30HIL E 1 »
B. Sudret, S. Marelli
263-2300-00LHow To Write Fast Numerical Code Information Restricted registration - show details
Number of participants limited to 84.

Prerequisite: Master student, solid C programming skills.
W6 credits3V + 2U
263-2300-00 VHow To Write Fast Numerical Code
Does not take place this semester.
3 hrsM. Püschel
263-2300-00 UHow To Write Fast Numerical Code
Does not take place this semester.
2 hrsM. Püschel
252-0526-00LStatistical Learning Theory Information W6 credits2V + 3P
252-0526-00 VStatistical Learning Theory2 hrs
Mon14:15-16:00ML H 44 »
J. M. Buhmann
252-0526-00 PStatistical Learning Theory3 hrs
Mon16:15-18:00ML H 44 »
J. M. Buhmann
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