Olivier Verscheure

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Housed at both EPFL and ETH Zurich, the newly created Swiss Data Science Center (SDSC) will address the fragmentation within today’s data and analytics landscapes. The SDSC will be composed of a distributed multi-disciplinary team of data scientists and experts in domains including personalized health and personalized medicine, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and computer scientists, and subject-matter experts around a cutting-edge analytics platform offering domain-specific “Insights-as-a-Service” while addressing security and privacy issues inherent to the field of data science. The unique synergy that the center will enable among the institutions of the ETH Domain and between academic and industrial stakeholders in both data science and across carefully selected domains is expected to foster scientific breakthroughs with significant societal impact. To accomplish this vision, the center will: (i) develop a network of embedded data science support to work closely with research groups and foster collaboration between users and data scientists; (ii) offer end-to-end data science services to the research and development communities in Switzerland and beyond, specifically a set of hosted software solutions to provide “Insights-as-a-Service”; (iii) create a community to share tools, methods and knowledge in the field.

INN 218 (Bâtiment INN)
Station 14
CH-1015 Lausanne

Web site: Web site: https://www.datascience.ch

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Teaching & PhD


Communication Systems

Computer Science


Lab in data science

This hands-on course teaches the tools & methods used by data scientists, from researching solutions to scaling up prototypes to Spark clusters. It exposes the students to the entire data science pipeline, from data acquisition to extracting valuable insights applied to real-world problems.

Data science for engineers with Python

This course is divided into two parts. The first part introduces the Python language and the notable differences between Python and C (used in the previous ICC course). The second part is an introduction to Python tools, libraries and collaborative methods in data science.