Search result: Courses in Autumn Semester 2021
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. | ||||||||||||
Seminar or Semester Paper | ||||||||||||
Number | Title | Type | ECTS | Hours | Lecturers | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
401-3620-20L | Student Seminar in Statistics: Inference in Some Non-Standard Regression Problems 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. | W | 4 credits | 2S | ||||||||
401-3620-00 S | Student Seminar in Statistics: Inference in Some Non-Standard Regression Problems Remark: former title in FS 2020: Student Seminar in Statistics: Inference in Non-Classical Regression Models | 2 hrs |
| F. Balabdaoui | ||||||||
401-3630-04L | Semester Paper Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required. For more information, see www.math.ethz.ch/intranet/students/study-administration/theses.html | W | 4 credits | 6A | ||||||||
401-3630-04 A | Semesterarbeit (Statistik) 4 KP | 80s hrs | by appt. | Supervisors | ||||||||
401-3630-06L | Semester Paper Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required. For more information, see www.math.ethz.ch/intranet/students/study-administration/theses.html | W | 6 credits | 9A | ||||||||
401-3630-06 A | Semesterarbeit (Statistik) 6 KP | 120s hrs | by appt. | Supervisors | ||||||||
252-5051-00L | Advanced Topics in Machine Learning Number of participants limited to 40. The deadline for deregistering expires at the end of the fourth week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | ||||||||
252-5051-00 S | Advanced Topics in Machine Learning | 2 hrs |
| J. M. Buhmann, R. Cotterell, J. Vogt, F. Yang |
- Page 1 of 1