263-3300-00L  Data Science Lab

SemesterAutumn Semester 2020
LecturersC. Zhang, V. Boeva, R. Cotterell, J. Vogt, F. Yang
Periodicityyearly recurring course
Language of instructionEnglish
CommentOnly for Data Science MSc.



Courses

NumberTitleHoursLecturers
263-3300-00 PData Science Lab
The lecturers will communicate the exact lesson times of ONLINE courses.
9 hrs
Thu14-16ON LI NE »
C. Zhang, V. Boeva, R. Cotterell, J. Vogt, F. Yang

Catalogue data

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.
Prerequisites / NoticePrerequisites: At least 8 KP must have been obtained under Data Analysis and at least 8 KP must have been obtained under Data Management and Processing.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits14 credits
ExaminersC. Zhang, V. Boeva, R. Cotterell, J. Vogt, F. Yang
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupData Science MSc (261000)

Offered in

ProgrammeSectionType
Data Science MasterData Science LabOInformation