Ce Zhang: Catalogue data in Autumn Semester 2017

Name Dr. Ce Zhang
URLhttps://zhangce.github.io/
DepartmentComputer Science
RelationshipAssociate Professor

NumberTitleECTSHoursLecturers
252-0817-00LDistributed Systems Laboratory Information
In the Master Programme max.10 credits can be accounted by Labs on top of the Interfocus Courses. These Labs will only count towards the Master Programme. 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 wireless networks, ad-hoc networks, RFID, and distributed applications on smartphones.
ObjectiveGain hands-on-experience with real products and the latest technology in 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 smartphones. The goal 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, see https://www.dsl.inf.ethz.ch/ or contact Prof. Mattern, Prof. Wattenhofer, Prof. Roscoe or Prof. G. Alonso.
263-3300-00LData Science Lab Information Restricted registration - show details
Number of participants limited to 30.

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 credits9PC. Zhang, K. Schawinski
AbstractIn this class, we bring together data science applications
provided by ETH researchers outside computer science and
teams of computer science master's students. Two to three
students will form a team working on data science/machine
learning-related research topics provided by scientists in
a diverse range of domains such as astronomy, biology,
social sciences etc.
ObjectiveThe goal of this class if for students to gain experience
of dealing with data science and machine learning applications
"in the wild". Students are expected to go through the full
process starting from data cleaning, modeling, execution,
debugging, error analysis, and quality/performance refinement.

Website: https://dslab.io
Prerequisites / NoticeEach student is required to send the lecturer their CV
and transcript and the lecturer will decide the enrollment
on a per-student basis. Moreover, the students are expected
to have experience about machine learning and deep learning.

EMAIL to send CV: ce.zhang@inf.ethz.ch
263-3504-00LHardware Acceleration for Data Processing Information 2 credits2SG. Alonso, T. Hoefler, O. Mutlu, C. Zhang
AbstractThe seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
ObjectiveThe seminar will cover topics related to data processing using new hardware in general and hardware accelerators (GPU, FPGA, specialized processors) in particular.
ContentThe general application areas are big data and machine learning. The systems covered will include systems from computer architecture, high performance computing, data appliances, and data centers.
Prerequisites / NoticeStudents taking this seminar should have the necessary background in systems and low level programming.