Search result: Course units in Spring Semester 2020
Statistics Master 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 | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|---|
401-6102-00L | Multivariate Statistics Does not take place this semester. | W | 4 credits | 2G | not available | |
401-0102-00L | Applied Multivariate Statistics | W | 5 credits | 2V + 1U | F. Sigrist | |
Time Series and Stochastic Processes | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
401-6624-11L | Applied Time Series | W | 5 credits | 2V + 1U | M. Dettling | |
Mathematical Statistics No offering in this semester | ||||||
Specialization Areas and Electives | ||||||
Statistical and Mathematical Courses | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
401-4632-15L | Causality | W | 4 credits | 2G | C. Heinze-Deml | |
401-4627-00L | Empirical Process Theory and Applications | W | 4 credits | 2V | S. van de Geer | |
401-3632-00L | Computational Statistics | W | 8 credits | 3V + 1U | M. H. Maathuis | |
401-3602-00L | Applied Stochastic Processes Does not take place this semester. | W | 8 credits | 3V + 1U | not available | |
401-3642-00L | Brownian Motion and Stochastic Calculus | W | 10 credits | 4V + 1U | W. Werner | |
401-6228-00L | Programming with R for Reproducible Research | W | 1 credit | 1G | M. Mächler | |
401-3629-00L | Quantitative Risk Management | W | 4 credits | 2V + 1U | P. Cheridito | |
401-4658-00L | Computational Methods for Quantitative Finance: PDE Methods | W | 6 credits | 3V + 1U | C. Schwab | |
401-2284-00L | Measure and Integration | W | 6 credits | 3V + 2U | F. Da Lio | |
401-3903-11L | Geometric Integer Programming | W | 6 credits | 2V + 1U | J. Paat | |
401-4944-20L | Mathematics of Data Science | W | 8 credits | 4G | A. Bandeira | |
227-0434-10L | Mathematics of Information | W | 8 credits | 3V + 2U + 2A | H. Bölcskei | |
261-5110-00L | Optimization for Data Science | W | 8 credits | 3V + 2U + 2A | B. Gärtner, D. Steurer | |
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 | A. Krause | |
252-0526-00L | Statistical Learning Theory | W | 7 credits | 3V + 2U + 1A | J. M. Buhmann, C. Cotrini Jimenez | |
252-3900-00L | Big Data for Engineers This course is not intended for Computer Science and Data Science MSc students! | W | 6 credits | 2V + 2U + 1A | G. Fourny | |
263-5300-00L | Guarantees for Machine Learning | W | 5 credits | 2V + 2A | F. Yang |
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