Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Ce Zhang: Catalogue data in Spring Semester 2019

Name Prof. Dr. Ce Zhang
FieldComputer Science
Address
Institut für Computing Platforms
ETH Zürich, STF K 513
Stampfenbachstrasse 114
8092 Zürich
SWITZERLAND
Telephone+41 44 632 75 29
E-mailce.zhang@inf.ethz.ch
URLhttps://ds3lab.inf.ethz.ch/members/ce-zhang.html
DepartmentComputer Science
RelationshipAssistant Professor (Tenure Track)

NumberTitleECTSHoursLecturers
252-0063-00LData Modelling and Databases Information 7 credits4V + 2UG. Alonso, C. Zhang
AbstractData modelling (Entity Relationship), relational data model, relational design theory (normal forms), SQL, database integrity, transactions and advanced database engines
ObjectiveIntroduction to relational databases and data management. Basics of SQL programming and transaction management.
ContentThe course covers the basic aspects of the design and implementation of databases and information systems. The courses focuses on relational databases as a starting point but will also cover data management issues beyond databases such as: transactional consistency, replication, data warehousing, other data models, as well as SQL.
LiteratureKemper, Eickler: Datenbanksysteme: Eine Einführung. Oldenbourg Verlag, 7. Auflage, 2009.

Garcia-Molina, Ullman, Widom: Database Systems: The Complete Book. Pearson, 2. Auflage, 2008.
252-0817-00LDistributed Systems Laboratory Information
In the Master Programme max. 10 credits can be accounted by Labs
on top of the Interfocus Courses. Additional Labs will be listed on the Addendum.
10 credits9PG. Alonso, T. Hoefler, F. Mattern, T. Roscoe, A. Singla, R. Wattenhofer, C. Zhang
AbstractThis course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including as well wireless networks, ad-hoc networks, and distributed application on mobile phones.
ObjectiveStudents acquire practical knowledge about technologies from the area of distributed systems.
ContentThis course involves the participation in a substantial development and/or evaluation project involving distributed systems technology. There are projects available in a wide range of areas: from web services to ubiquitous computing including as well wireless networks, ad-hoc networks, and distributed application on mobile phones. The objecte of the project is for the students to gain hands-on-experience with real products and the latest technology in distributed systems. There is no lecture associated to the course.
For information of the course or projects available, please contact Prof. Mattern, Prof. Wattenhofer, Prof. Roscoe or Prof. G. Alonso.
263-3840-00LHardware Architectures for Machine Learning Information
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.
2 credits2SG. Alonso, T. Hoefler, C. Zhang
AbstractThe seminar covers recent results in the increasingly important field of hardware acceleration for data science and machine learning, both in dedicated machines or in data centers.
ObjectiveThe seminar aims at students interested in the system aspects of machine learning, who are willing to bridge the gap across traditional disciplines: machine learning, databases, systems, and computer architecture.
ContentThe seminar is intended to cover recent results in the increasingly important field of hardware acceleration for data science and machine learning, both in dedicated machines or in data centers.
Prerequisites / NoticeThe seminar should be of special interest to students intending to complete a master's thesis or a doctoral dissertation in related topics.