Search result: Courses in Spring Semester 2020

Statistics Master Information
The following courses belong to the curriculum of the Master's Programme in Statistics. The corresponding credits do not count as external credits even for course units where an enrolment at ETH Zurich is not possible.
Core Courses
In each subject area, the core courses offered are normally mathematical as well as application-oriented in content. For each subject area, only one of these is recognised for the Master degree.
No offering in this semester (401-3622-00L Statistical Modelling is offered in the autumn semester).
Analysis of Variance and Design of Experiments
No offering in this semester
Multivariate Statistics
401-6102-00LMultivariate StatisticsW4 credits2G
401-6102-00 GMultivariate Statistics
Does not take place this semester.
2 hrsnot available
401-0102-00LApplied Multivariate StatisticsW5 credits2V + 1U
401-0102-00 VApplied Multivariate Statistics2 hrs
Mon15-17ER SA TZ »
15-17HG F 3 »
F. Sigrist
401-0102-00 UApplied Multivariate Statistics1 hrs
Mon/2w08-10ER SA TZ »
08-10HG D 1.1 »
F. Sigrist
Time Series and Stochastic Processes
401-6624-11LApplied Time SeriesW5 credits2V + 1U
401-6624-11 VApplied Time Series2 hrs
Mon10-12ER SA TZ »
10-12HG E 1.1 »
M. Dettling
401-6624-11 UApplied Time Series1 hrs
Mon/2w08-10ER SA TZ »
08-10HG D 1.1 »
M. Dettling
Mathematical Statistics
No offering in this semester
Specialization Areas and Electives
Statistical and Mathematical Courses
401-4632-15LCausality Information W4 credits2G
401-4632-15 GCausality2 hrs
Wed10-12ER SA TZ »
10-12HG E 1.1 »
C. Heinze-Deml
401-4627-00LEmpirical Process Theory and ApplicationsW4 credits2V
401-4627-00 VEmpirical Process Theory and Applications2 hrs
Thu08-10ER SA TZ »
08-10HG D 1.2 »
S. van de Geer
401-3632-00LComputational StatisticsW8 credits3V + 1U
401-3632-00 VComputational Statistics3 hrs
Thu13-15ER SA TZ »
13-15HG F 1 »
Fri09-10ER SA TZ »
09-10NO C 60 »
M. H. Maathuis
401-3632-00 UComputational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG G 5.
1 hrs
Fri10-11ER SA TZ »
10-11HG G 5 »
M. H. Maathuis
401-3602-00LApplied Stochastic Processes Information W8 credits3V + 1U
401-3602-00 VApplied Stochastic Processes
Does not take place this semester.
3 hrsnot available
401-3602-00 UApplied Stochastic Processes
Does not take place this semester.
1 hrsnot available
401-3642-00LBrownian Motion and Stochastic Calculus Information W10 credits4V + 1U
401-3642-00 VBrownian Motion and Stochastic Calculus
Lectures will be recorded and published weekly on the Videoportal (
4 hrs
Wed08-10ER SA TZ »
08-10HG E 5 »
Thu10-12ER SA TZ »
10-12ETF C 1 »
W. Werner
401-3642-00 UBrownian Motion and Stochastic Calculus
Groups are selected in myStudies.
See at
1 hrs
Fri08-09HG G 26.5 »
09-10HG G 26.5 »
12-13HG G 26.3 »
W. Werner
401-6228-00LProgramming with R for Reproducible Research Information W1 credit1G
401-6228-00 GProgramming with R for Reproducible Research14s hrs
Tue/114-16HG E 1.1 »
07.04.14-16HG E 1.1 »
21.08.14-16HG D 3.2 »
M. Mächler
401-3629-00LQuantitative Risk Management Information W4 credits2V + 1U
401-3629-00 VQuantitative Risk Management
Recorded lectures will be posted in the material section of the QRM website
2 hrs
Thu10-12ER SA TZ »
10-12ML H 44 »
P. Cheridito
401-3629-00 UQuantitative Risk Management
The QRM lecture and exercise session of March 12 will not take place in the auditorium. A video lecture will be made available on
1 hrs
Thu12-13ER SA TZ »
12-13ML H 44 »
P. Cheridito
401-4658-00LComputational Methods for Quantitative Finance: PDE Methods Information Restricted registration - show details W6 credits3V + 1U
401-4658-00 VComputational Methods for Quantitative Finance: PDE Methods
Permission from lecturers required for all students.
3 hrs
Wed13-15HG D 5.2 »
Fri14-15HG D 5.2 »
13.03.14-15HG D 7.1 »
C. Schwab
401-4658-00 UComputational Methods for Quantitative Finance: PDE Methods
Groups are selected in myStudies.
1 hrs
Fri13-14HG D 5.2 »
15-16HG D 5.2 »
13.03.13-14HG D 7.1 »
15-16HG D 7.1 »
C. Schwab
401-2284-00LMeasure and Integration Information W6 credits3V + 2U
401-2284-00 VMass und Integral (Measure and Integration)
Die Vorlesungen finden ab dem 4. März 2020 bis Semesterende ohne Publikum statt.
3 hrs
Wed09-10ER SA TZ »
09-10HG F 3 »
Fri10-12ER SA TZ »
10-12HG F 3 »
F. Da Lio
401-2284-00 UMass und Integral
Groups are selected in myStudies.
Einige Übungsgruppen werden auf Deutsch gehalten.
Some exercise classes will be held in English.
Für die Übungen vom 4. März 2020 siehe
2 hrs
Wed10-12HG E 33.5 »
10-12HG G 26.1 »
10-12LEE D 105 »
10-12ML F 40 »
10-12ML H 43 »
10-12ML J 34.1 »
F. Da Lio
401-3903-11LGeometric Integer ProgrammingW6 credits2V + 1U
401-3903-11 VGeometric Integer Programming2 hrs
Thu13-15HG E 33.3 »
J. Paat
401-3903-11 UGeometric Integer Programming1 hrs
Wed12-13HG E 33.3 »
J. Paat
401-4944-20LMathematics of Data ScienceW8 credits4G
401-4944-20 GMathematics of Data Science
Planned to take place again in the Autumn Semester 2021.
4 hrs
Tue15-17HG F 7 »
Thu15-17HG G 3 »
A. Bandeira
227-0434-10LMathematics of Information Information W8 credits3V + 2U + 2A
227-0434-10 VMathematics of Information3 hrs
Thu09-12ETZ E 6 »
H. Bölcskei
227-0434-10 UMathematics of Information2 hrs
Mon13-15ETZ E 6 »
H. Bölcskei
227-0434-10 AMathematics of Information2 hrsH. Bölcskei
261-5110-00LOptimization for Data Science Information W8 credits3V + 2U + 2A
261-5110-00 VOptimization for Data Science3 hrs
Mon15-16ER SA TZ »
15-16ETF C 1 »
Tue10-12ER SA TZ »
10-12ETF C 1 »
B. Gärtner, D. Steurer
261-5110-00 UOptimization for Data Science2 hrs
Tue13-15HG D 3.2 »
13-15HG D 5.2 »
B. Gärtner, D. Steurer
261-5110-00 AOptimization for Data Science2 hrsB. Gärtner, D. Steurer
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 in this regard. If necessary, please contact
W8 credits4V + 2U + 1A
252-0220-00 VIntroduction to Machine Learning
FS20 CORONA: Keine Aufzeichnung / 17.03.20 rb
4 hrs
Tue13-15ER SA TZ »
13-15ETA F 5 »
13-15ETF E 1 »
Wed13-15ER SA TZ »
13-15ETA F 5 »
13-15ETF E 1 »
A. Krause
252-0220-00 UIntroduction to Machine Learning2 hrs
Wed15-17CAB G 61 »
15-17ER SA TZ »
17-19CAB G 61 »
17-19ER SA TZ »
Fri13-15ER SA TZ »
13-15ML D 28 »
A. Krause
252-0220-00 AIntroduction to Machine Learning
No presence required.
1 hrsA. Krause
252-0526-00LStatistical Learning Theory Information W7 credits3V + 2U + 1A
252-0526-00 VStatistical Learning Theory3 hrs
Mon14-16ER SA TZ »
14-16HG G 3 »
Tue17-18ER SA TZ »
17-18HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 UStatistical Learning Theory2 hrs
Mon16-18ER SA TZ »
16-18HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 AStatistical Learning Theory1 hrsJ. M. Buhmann, C. Cotrini Jimenez
252-3900-00LBig Data for Engineers Information
This course is not intended for Computer Science and Data Science MSc students!
W6 credits2V + 2U + 1A
252-3900-00 VBig Data for Engineers2 hrs
Tue10-12ER SA TZ »
10-12HG G 5 »
G. Fourny
252-3900-00 UBig Data for Engineers
Groups are selected in myStudies.
2 hrs
Wed14-16CAB G 57 »
15-17ML H 34.3 »
15-17NO C 44 »
16-18NO D 11 »
Fri15-17CAB G 56 »
15-17CAB G 57 »
G. Fourny
252-3900-00 ABig Data for Engineers1 hrsG. Fourny
263-5300-00LGuarantees for Machine Learning Information Restricted registration - show details W5 credits2V + 2A
263-5300-00 VGuarantees for Machine Learning
Special selection process. Preference is given to Masters and Doctorate students. If need be other criteria are degree program and previous courses taken.
2 hrs
Wed08-10CAB G 51 »
F. Yang
263-5300-00 AGuarantees for Machine Learning2 hrsF. Yang
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