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.
Regression
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
NumberTitleTypeECTSHoursLecturers
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
Mon15:00-17:00ER SA TZ »
15:15-17:00HG F 3 »
F. Sigrist
401-0102-00 UApplied Multivariate Statistics1 hrs
Mon/2w08:00-10:00ER SA TZ »
08:15-10:00HG D 1.1 »
F. Sigrist
Time Series and Stochastic Processes
NumberTitleTypeECTSHoursLecturers
401-6624-11LApplied Time SeriesW5 credits2V + 1U
401-6624-11 VApplied Time Series2 hrs
Mon10:00-12:00ER SA TZ »
10:15-12:00HG E 1.1 »
M. Dettling
401-6624-11 UApplied Time Series1 hrs
Mon/2w08:00-10:00ER SA TZ »
08:15-10:00HG D 1.1 »
M. Dettling
Mathematical Statistics
No offering in this semester
Specialization Areas and Electives
Statistical and Mathematical Courses
NumberTitleTypeECTSHoursLecturers
401-4632-15LCausality Information W4 credits2G
401-4632-15 GCausality2 hrs
Wed10:00-12:00ER SA TZ »
10:15-12:00HG E 1.1 »
C. Heinze-Deml
401-4627-00LEmpirical Process Theory and ApplicationsW4 credits2V
401-4627-00 VEmpirical Process Theory and Applications2 hrs
Thu08:00-10:00ER SA TZ »
08:15-10:00HG D 1.2 »
S. van de Geer
401-3632-00LComputational StatisticsW8 credits3V + 1U
401-3632-00 VComputational Statistics3 hrs
Thu13:00-15:00ER SA TZ »
13:15-15:00HG F 1 »
Fri09:00-10:00ER SA TZ »
09:15-10:00NO 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
Fri10:00-11:00ER SA TZ »
10:15-11:00HG 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 (Link)
4 hrs
Wed08:00-10:00ER SA TZ »
08:15-10:00HG E 5 »
Thu10:00-12:00ER SA TZ »
10:15-12:00ETF C 1 »
W. Werner
401-3642-00 UBrownian Motion and Stochastic Calculus
Groups are selected in myStudies.
See at Link
1 hrs
Fri08:15-09:00HG G 26.5 »
09:15-10:00HG G 26.5 »
12:15-13:00HG 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/114:15-16:00HG E 1.1 »
07.04.14:15-16:00HG E 1.1 »
21.08.14:15-16:00HG 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 Link
2 hrs
Thu10:00-12:00ER SA TZ »
10:15-12:00ML 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 Link
1 hrs
Thu12:00-13:00ER SA TZ »
12:15-13:00ML 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
Wed13:15-15:00HG D 5.2 »
Fri14:15-15:00HG D 5.2 »
13.03.14:15-15:00HG D 7.1 »
C. Schwab
401-4658-00 UComputational Methods for Quantitative Finance: PDE Methods
Groups are selected in myStudies.
1 hrs
Fri13:15-14:00HG D 5.2 »
15:15-16:00HG D 5.2 »
13.03.13:15-14:00HG D 7.1 »
15:15-16:00HG 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
Wed09:00-10:00ER SA TZ »
09:15-10:00HG F 3 »
Fri10:00-12:00ER SA TZ »
10:15-12:00HG 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 Link
2 hrs
Wed10:15-12:00HG E 33.5 »
10:15-12:00HG G 26.1 »
10:15-12:00LEE D 105 »
10:15-12:00ML F 40 »
10:15-12:00ML H 43 »
10:15-12:00ML J 34.1 »
F. Da Lio
401-3903-11LGeometric Integer ProgrammingW6 credits2V + 1U
401-3903-11 VGeometric Integer Programming2 hrs
Thu13:15-15:00HG E 33.3 »
J. Paat
401-3903-11 UGeometric Integer Programming1 hrs
Wed12:15-13:00HG 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
Tue15:15-17:00HG F 7 »
Thu15:15-17:00HG G 3 »
A. Bandeira
227-0434-10LMathematics of Information Information W8 credits3V + 2U + 2A
227-0434-10 VMathematics of Information3 hrs
Thu09:15-12:00ETZ E 6 »
H. Bölcskei
227-0434-10 UMathematics of Information2 hrs
Mon13:15-15:00ETZ 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
Mon15:00-16:00ER SA TZ »
15:15-16:00ETF C 1 »
Tue10:00-12:00ER SA TZ »
10:15-12:00ETF C 1 »
B. Gärtner, D. Steurer
261-5110-00 UOptimization for Data Science2 hrs
Tue13:15-15:00HG D 3.2 »
13:15-15:00HG 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 Link
W8 credits4V + 2U + 1A
252-0220-00 VIntroduction to Machine Learning
FS20 CORONA: Keine Aufzeichnung / 17.03.20 rb
4 hrs
Tue13:00-15:00ER SA TZ »
13:15-15:00ETA F 5 »
13:15-15:00ETF E 1 »
Wed13:00-15:00ER SA TZ »
13:15-15:00ETA F 5 »
13:15-15:00ETF E 1 »
A. Krause
252-0220-00 UIntroduction to Machine Learning2 hrs
Wed15:00-17:00ER SA TZ »
15:15-17:00CAB G 61 »
17:00-19:00ER SA TZ »
17:15-19:00CAB G 61 »
Fri13:00-15:00ER SA TZ »
13:15-15:00ML 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
Mon14:00-16:00ER SA TZ »
14:15-16:00HG G 3 »
Tue17:00-18:00ER SA TZ »
17:15-18:00HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 UStatistical Learning Theory2 hrs
Mon16:00-18:00ER SA TZ »
16:15-18:00HG 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
Tue10:00-12:00ER SA TZ »
10:15-12:00HG G 5 »
G. Fourny
252-3900-00 UBig Data for Engineers
Groups are selected in myStudies.
2 hrs
Wed14:15-16:00CAB G 57 »
15:15-17:00ML H 34.3 »
15:15-17:00NO C 44 »
16:15-18:00NO D 11 »
Fri15:15-17:00CAB G 56 »
15:15-17:00CAB 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
Wed08:15-10:00CAB G 51 »
F. Yang
263-5300-00 AGuarantees for Machine Learning2 hrsF. Yang
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.
Lecture will be streamed and recorded
2 hrs
Thu12:00-14:00ER SA TZ »
12:15-14:00BSB 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
Thu14:00-15:00ER SA TZ »
14:15-15:00BSB 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
701-0104-00LStatistical Modelling of Spatial DataW3 credits2G
701-0104-00 GStatistical Modelling of Spatial Data2 hrs
Wed08:15-10:00CHN F 46 »
A. J. Papritz
401-6222-00LRobust and Nonlinear Regression Information Restricted registration - show details W2 credits1V + 1U
401-6222-00 VRobust and Nonlinear Regression Special students and auditors need a special permission from the lecturers.
Block course
12s hrs
08.06.08:15-10:00HG D 1.2 »
13:15-15:00HG D 1.2 »
15.06.08:15-10:00HG D 1.2 »
13:15-15:00HG D 1.2 »
22.06.08:15-10:00HG D 1.2 »
13:15-15:00HG D 1.2 »
A. F. Ruckstuhl
401-6222-00 URobust and Nonlinear Regression Special students and auditors need a special permission from the lecturers.
Block course
9s hrs
08.06.10:15-12:00HG D 1.2 »
15:15-17:00HG D 1.2 »
15.06.10:15-12:00HG D 1.2 »
15:15-17:00HG D 1.2 »
22.06.10:15-12:00HG D 1.2 »
15:15-17:00HG D 1.2 »
A. F. Ruckstuhl
401-8618-00LStatistical Methods in Epidemiology (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: STA408

Mind the enrolment deadlines at UZH:
Link
W5 credits3G
401-8618-00 GStatistical Methods in Epidemiology (University of Zurich)
**Course at University of Zurich**
3 hrs
Mon09:00-12:00UNI ZH .
University lecturers
401-4626-00LAdvanced Statistical Modelling: Mixed ModelsW4 credits2V
401-4626-00 VAdvanced Statistical Modelling: Mixed Models2 hrs
Tue08:15-10:00HG F 26.5 »
M. Mächler
447-6236-00LStatistics for Survival Data Restricted registration - show details W2 credits1V + 1U
447-6236-00 VStatistics for Survival Data Special students and auditors need a special permission from the lecturers.
Block course
10s hrs
Mon08:15-10:00HG G 19.1 »
13:15-15:00HG G 19.1 »
A. Hauser
447-6236-00 UStatistics for Survival Data Special students and auditors need a special permission from the lecturers.
Block course.
7.5s hrs
Mon10:15-12:00HG G 19.1 »
15:15-17:00HG G 19.1 »
A. Hauser
401-8628-00LSurvival Analysis (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: STA425

Mind the enrolment deadlines at UZH:
Link
W3 credits1.5G
401-8628-00 GSurvival Analysis
**Course at University of Zurich**
1.5 hrs
Tue/109:00-12:00UNI ZH .
University lecturers
Application Areas
Students select one area of application and look for suitable courses in which quantitative methods and modeling play a role. They need the consent by the Advisor (Link) that the chosen courses are eligible in the category "Application Areas".

For the category assignment of eligible courses keep the choice "no category" and take contact with the Study Administration Office (Link) after having received the credits. The Study Administration Office needs the Advisor's consent.
Seminar or Semester Paper
NumberTitleTypeECTSHoursLecturers
401-4620-00LStatistics Lab Restricted registration - show details
Number of participants limited to 27.
W6 credits2S
401-4620-00 SStatistics Lab
Substantial additional time is required for attending the consulting sessions, carrying out the data analysis and writing of the report. The dates/times for the sessions are arranged on an individual basis. More information is given during the first seminar lecture.
2 hrs
Wed15:15-17:00HG E 33.1 »
04.03.15:15-17:00HG F 7 »
11.03.15:15-17:00HG F 7 »
18.03.15:15-17:00HG F 7 »
M. Kalisch, M. H. Maathuis, M. Mächler, L. Meier, N. Meinshausen
401-3630-04LSemester Paper Restricted registration - show details
Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required.
For more information, see Link
W4 credits6A
401-3630-04 ASemesterarbeit (Statistik) 4 KP Special students and auditors need a special permission from the lecturers.80s hrsby appt.Supervisors
401-3630-94LSemester Paper Restricted registration - show details
Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required.
For more information, see Link
W4 credits6A
401-3630-94 ASemesterarbeit (Statistik) 4 KP Special students and auditors need a special permission from the lecturers.80s hrsby appt.Supervisors
401-3630-06LSemester Paper Restricted registration - show details
Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required.
For more information, see Link
W6 credits9A
401-3630-06 ASemesterarbeit (Statistik) 6 KP Special students and auditors need a special permission from the lecturers.120s hrsby appt.Supervisors
401-3620-20LStudent Seminar in Statistics: Inference in Non-Classical Regression Models Restricted registration - show details
Number of participants limited to 24.
Mainly for students from the Mathematics Bachelor and Master Programmes who, in addition to the introductory course unit 401-2604-00L Probability and Statistics, have heard at least one core or elective course in statistics. Also offered in the Master Programmes Statistics resp. Data Science.
W4 credits2S
401-3620-00 SStudent Seminar in Statistics: Inference in Non-Classical Regression Models2 hrs
Mon15:15-17:00HG E 33.1 »
F. Balabdaoui
401-3940-20LStudent Seminar in Mathematics and Data: Optimization of Random Functions Restricted registration - show details
Number of participants limited to 12.
W4 credits2S
401-3940-00 SStudent Seminar in Mathematics and Data: Optimization of Random Functions2 hrs
Thu13:15-15:00HG G 3 »
A. Bandeira
363-1100-00LRisk Case Study Challenge Restricted registration - show details W3 credits2S
363-1100-00 SRisk Case Study Challenge Special students and auditors need a special permission from the lecturers.
Does not take place this semester.
2 hrsA. Bommier, S. Feuerriegel
GESS Science in Perspective
Two credits are needed from the "Science in Perspective" programme with language courses excluded if three credits from language courses have already been recognised for the Bachelor's degree.
see Link (Eight credits must be acquired in this category: normally six during the Bachelor’s degree programme, and two during the Master’s degree programme. A maximum of three credits from language courses from the range of the Language Center of the University of Zurich and ETH Zurich may be recognised. In addition, only advanced courses (level B2 upwards) in the European languages English, French, Italian and Spanish are recognised. German language courses are recognised from level C2 upwards.)
» see Science in Perspective: Type A: Enhancement of Reflection Capability
» Recommended Science in Perspective (Type B) for D-MATH
» see Science in Perspective: Language Courses ETH/UZH
Master's Thesis
NumberTitleTypeECTSHoursLecturers
401-2000-00LScientific Works in Mathematics
Target audience:
Third year Bachelor students;
Master students who cannot document to have received an adequate training in working scientifically.
O0 credits
401-2000-00 VScientific Works in Mathematics
Groups are selected in myStudies.
This mandatory course is offered twice per semester.
For the performance of 27 February: Carry your ETH student card with you to prove your identity.
For the performance of 14 May: The exact specifications for online presence at the zoom meeting will be announced in due course (Professor Kowalski will send an email).
1s hrs
27.02.18:15-19:00HG G 3 »
14.05.18:15-19:00HG G 3 »
Ö. Imamoglu, E. Kowalski
401-2000-01LLunch Sessions – Thesis Basics for Mathematics Students
Details and registration for the optional MathBib training course: Link
Z0 credits
401-2000-01 GLunch Sessions – Thesis Basics für Mathematik-Studierende2s hrsSpeakers
401-4990-02LMaster's Thesis Restricted registration - show details
Only students who fulfil the following criteria are allowed to begin with their Master's thesis:
a. successful completion of the Bachelor's programme;
b. fulfilling of any additional requirements necessary to gain admission to the Master's programme;
c. They have acquired at least 16 credits in the category ‘Core courses‘.

Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required.
For more information, see Link
O30 credits57D
401-4990-02 DMaster's Thesis (Statistics) Special students and auditors need a special permission from the lecturers.800s hrsby appt.Supervisors
Course Units for Additional Admission Requirements
The courses below are only available for MSc students with additional admission requirements.
NumberTitleTypeECTSHoursLecturers
406-0173-AALLinear Algebra I and II
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-6 credits13R
406-0173-AA RLinear Algebra I and II
Self-study course. No presence required.
180s hrsN. Hungerbühler
406-0243-AALAnalysis I and II Information
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-14 credits30R
406-0243-AA RAnalysis I and II
Self-study course. No presence required.
420s hrsM. Akveld
406-0603-AALStochastics (Probability and Statistics)
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-4 credits9R
406-0603-AA RStochastics (Probability and Statistics)
Self-study course. No presence required.
120s hrsM. Kalisch
406-2604-AALProbability and Statistics
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-7 credits15R
406-2604-AA RProbability and Statistics
Self-study course. No presence required.
210s hrsM. Schweizer