The spring semester 2021 will take place online until further notice. Exceptions: Courses that can only be carried out with on-site presence. Please note the information provided by the lecturers.

851-0585-38L  Data Science in Techno-Socio-Economic Systems

SemesterSpring Semester 2016
LecturersE. Pournaras, D. Helbing, I. Moise
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to 70.

This course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulations.

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



Catalogue data

AbstractThis course introduces how techno-socio-economic systems in our nowadays digital society can be better understood with techniques and tools of data science. Students shall learn the fundamentals of data science, machine learning, but also advanced distributed real-time data analytics in the Planetary Nervous System. Students shall deliver and present a seminar thesis at the end of the course.
ObjectiveThe goal of this course is to qualify students with knowledge on data science as a way to understand complex techno-socio-economic systems in our nowadays digital societies. This course aims to make students capable of applying the most appropriate and effective techniques of data science under different application scenarios. The course aims to engage students in exciting state-of-the-art scientific and collaboration platforms such as the Planetary Nervous System. The course shall increase the awareness level of students about the challenges and open issues of data science in socio-technical domains such as privacy. Finally students have the opportunity to develop their writing, presentation and collaboration skills based on a seminar thesis they have to deliver and present at the end of the course

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersD. Helbing, I. Moise, E. Pournaras
Typegraded 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.

Courses

NumberTitleHoursLecturers
851-0585-38 VData Science in Techno-Socio-Economic Systems2 hrs
Mon17-19LFW B 1 »
E. Pournaras, D. Helbing, I. Moise

Groups

No information on groups available.

Restrictions

Places70 at the most
Waiting listuntil 13.02.2016

Offered in

ProgrammeSectionType
GESS Compulsory Elective CourseD-INFKWInformation
GESS Compulsory Elective CourseSociologyWInformation
GESS Compulsory Elective CourseD-ITETWInformation
GESS Compulsory Elective CourseD-MTECWInformation
GESS Compulsory Elective CourseD-MAVTWInformation
GESS Compulsory Elective CourseD-PHYSWInformation
Science, Technology, and Policy MasterElectivesWInformation