Search result: Course units in Spring Semester 2020

Previously "Energy-Efficient Parallel Computing Systems for Data Analytics"

Registration in this class requires the permission of the instructors. Class size will be limited to 30.
Preference is given to students in the MSc EEIT.

Does not take place this semester.

Registration in this class requires the permission of the instructors. Class size will be limited to 80 students.
Preference is given to EEIT, INF and RSC students.

Does not take place this semester.
Takes place in HS20.

Only for Data Science MSc.

Only for master students, otherwise a special permission by the study administration of D-INFK is required.

Only for master students, otherwise a special permission by the study administration of D-INFK is required.

Number of participants limited to 200.

Number of participants limited to 30.

Not meant for BSc/MSc students of mathematics.

Does not take place this semester.

Does not take place this semester.

This theory part QIP I together with the experimental part 402-0448-02L QIP II (both offered in the Spring Semester) combine to the core course in experimental physics "Quantum Information Processing" (totally 10 ECTS credits). This applies to the Master's degree programme in Physics.

Prerequisite: Successful completion of Cartography III (103-0227-00L).

This course is part II of a two-semester course.
Knowledge of part I is required.

Basic knowledge of computer vision would be helpful.

Number of participants limited to 20.

Number of participants limited to 150.

No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: MFOEC207

Mind the enrolment deadlines at UZH:
https://www.uzh.ch/cmsssl/en/studies/application/mobilitaet.html

A related course is 401-3913-01L Mathematical Foundations for Finance (3V+2U, 4 ECTS credits). Although both courses can be taken independently of each other, only one will be recognised for credits in the Bachelor and Master degree. In other words, it is not allowed to earn credit points with one for the Bachelor and with the other for the Master degree.

No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: MFOEC206

Mind the enrolment deadlines at UZH:
https://www.uzh.ch/cmsssl/en/studies/application/mobilitaet.html

This course is intended for students interested in data analysis and with basic knowledge of inferential statistics.

Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module INI405 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link

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:
https://www.uzh.ch/cmsssl/en/studies/application/mobilitaet.html

Particularly suitable for students of D-INFK, D-ITET, D-MTEC

This is the optional course project for "Building a Robot Judge: Data Science for the Law."

Please register only if attending the lecture course or with consent of the instructor.

Some programming experience in Python is required, and some experience with text mining is highly recommended.

Number of participants limited to 35

Students will be informed by 1.3.2020 at the latest.

Does not take place this semester.

Number of participants limited to 20.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.

Number of participants limited to 20.

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.

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.

Number of participants limited to 35

Students will be informed by 1.3.2020 at the latest.

The minimal prerequisites for the Master’s thesis registration are:
- Completed Bachelor’s program
- All additional requirements completed (additional requirements, if any, are listed in the admission decree)
- Minimum degree requirements fulfilled of the course categories Data Analysis and Data Management and overall 50 credits obtained in the course category Core Courses
- Data Science Lab (14 credits) completed