Chandrasekhar studied mathematics at the University of California, Berkeley (B.A. 1997) and art and computer science at the University of California, Santa Barbara (M.A. 2003). He has worked as a software developer and consultant for companies, research institutions, and NGOs in the US, Germany, and Switzerland. Since 2009, he has been at ETH Zürich supporting projects by developing software solutions for data management, analysis, and visualization. In addition to his work at ETH, he teaches data visualization at Propulsion Academy and, as Illposed works on artistic projects that incorporate data as a central component.
Reproducible Data Science in Python
In this tutorial, we will take a detailed look at the concept of reproducibility, survey the landscape of existing solutions, and, using one solution in particular, Renku, we will do some hands-on work.