Thursday, October 17th from 11-12
Business Silo (003-213)
Abstract
Data Science as a field is being driven by increased demand for statistical applications across disciplines, increased quality of digital information, computing capacity to handle that information, increasing scope of open source software and open science approaches throughout various fields. Teaching this often requires elements of computer science coding and statistical inference at the same time.
This evolution in data science education will bring significant benefits in domain fields outside of computer science such as Engineering, Social Sciences, Economics, Political Science, Sociology, Environmental Sciences, Biology, Chemistry, and others.
UC Berkeley created a large and popular introductory class in coding and statistics, accessible to all students at the University, and is a replacement for a statistics prerequisite that many majors have. A significant amount of curricular development and engineering of cloud infrastructure was needed to allow any student to access the computing in a browser window. This open source stack of technology has allowed us to scale the teaching approach to a wide variety of classes and broaden the population of students who can do labs and assignments in this data science environment. The key software elements are the use of Jupyter notebooks delivered through interactive links on a Jupyterhub.
The hurdles encountered in developing this curriculum and the benefits of this pedagogical approach will be presented.
Bio
Dr. Eric Van Dusen is the Director of Curriculum in the Division of Data Science and Information at the University of California at Berkeley. Eric has a BS from UC Berkeley and a PhD from UC Davis in Agricultural and Resource Economics, with specialization in International Development and in Econometrics. He has worked internationally in Mexico and Central America, in Uzbekistan in Central Asia, and in Kenya in East Africa. Hi is currently working on a broad interdisciplinary effort to expand the offerings of data science throughout UC Berkeley, from helping with the development of a new major and a new minor in Data Science, to overseeing a set of Data Science Connectors, leading a team developing Data Science modules for a broad range of existing classes, and working to create new materials in his own classes.
