"The future of data science education is plain text"
Monday, May 21st, 2018 – 1:00pm - 2:00pm
Jeff Leek, Department of Biostatistics, Johns Hopkins
Abstract: Data science is the process of formulating a quantitative question that can be answered with data, collecting and cleaning the data, analyzing the data and communicating the answer to the question to the relevant audience. I'll discuss the common (math, programming) and less common (question formulation, data pipelines) components of data science. I will use examples from our experience creating and maintaining more than 20 data science courses that have enrolled more than 4 million over the last 4 years to illustrate why the future of data science courses is based on plain text documents.
Bio: Jeff Leek is a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health. His research focuses on public health genomics, data science as a science, and research on the scientific literature. He is also co-creator of the Johns Hopkins Data Science Specialization on Coursera (https://www.coursera.org/specializations/jhu-data-science) that has enrolled over 4 million students. He is a co-editor of the journal Biostatistics. He writes a blog at Simply Statistics and is the author of the book "The Elements of Data Analytic Style".
"Data Science for all!! Sure! But when, where, how, and why?"
Wednesday, May 23rd, 2018 – 1:00pm - 2:00pm
Richard DeVeaux, Department of Mathematics and Statistics, Williams College
Abstract: With all the hype about data science and the pressure from university administrators to teach it, it's tempting to dive headfirst into the data science pool. But maybe we should first check the water temperature, or see if in fact, there's any water there at all. How much of the data science tools should we teach in the first course? The group at the Park City Math Institute wrote some preliminary guidelines for undergraduate data science curricula. We'll examine their recommendations and talk about how the introductory course in statistics fits into the program.
Bio: Richard De Veaux, Ph.D. (Dick) is C. Carlise and Margaret Tippit Professor of Statistics at Williams College. He holds degrees in Civil Engineering (B.S.E. Princeton), Mathematics (A.B. Princeton), Dance Education (M.A. Stanford) and Statistics (Ph.D., Stanford), where he studied statistics with Persi Diaconis, and dances with Inga Weiss. Dick has taught at the Wharton School and the Engineering School at Princeton and has been a visiting researcher at INRA in Montpellier and a visiting professor at Paris V. De Veaux has won numerous teaching awards from the Engineering Council at Princeton. He has won both the Wilcoxon and Shewell (twice) awards from the American Society for Quality, is a fellow of the American Statistical Assoc (ASA) and an elected member of the ISI. He has served on the Board of Directors of the ASA and is the past chair of the Section on Statistical Learning and Data Science.
Dick has been a consultant for nearly 30 years for such Fortune 500 companies as Hewlett-Packard, Alcoa, American Express, Bank One, GlaxoSmithKline, Dupont, Pillsbury, SanofiPasteur and General Electric. He holds two U.S. patents and is the author of more than 40 refereed journal articles. He once helped Mickey Hart of the Grateful Dead with the question How many drummers are there in the world and for that he is know as the Official Statistician of the Grateful Dead. He is the co-author, with Paul Velleman and David Bock, of the critically acclaimed textbooks Intro Stats, Stats: Modeling the World and Stats: Data and Models and with Norean Sharpe and Paul Velleman of Business Statistics , and Business Statistics: A First Course, all published by Pearson.