Data Science is a rapidly emerging discipline at the intersection of statistics, machine learning, data visualization, and mathematical modeling. This course is designed to provide a hands-on introduction to Data Science by challenging student groups to build predictive models for upcoming events, and validating their models against the actual outcomes.
We will use a preliminary manuscript of my forthcoming book “The Data Science Design Manual”, with a target date for publication of August 2017. Copies of the manuscript will be available for purchase at cost (about $25) from the Stony Brook campus UPS store, located on the lower level of Melville Library - E0320. Phone: (631) 632-1831
I will welcome feedback on the book, and corrections to the manuscript at the end of the semester, so please denote them clearly (with a highlighter?) in your copy as you read it. Extra credit will be awarded to students who report substantial amounts of corrections especially on chapters (ID mod 12) +1 and (ID mod 12)+7, so I get feedback on everything.
I will give about 25 formal lectures this semester. All classes will be filmed by Echo360 and made available on Blackboard.
Old lecture notes are available from the previous offering in Fall 2014.
Roughly half of the course grade will come from a course project. Students will typically work in small groups (2-3 people) on independent research projects. I will distribute a list of possible projects about six weeks into the semester. You will be encouraged to develop your own project ideas, although I must approve.
The field of data science is still emerging, but there are several books which it will be useful to read and consult:
Steven S. Skiena 251 New Computer Science Building Department of Computer Science Stony Brook University Stony Brook, NY 11794-2424, USA firstname.lastname@example.org 631-632-9026