CS 47N: Datathletics: Diving into Data Analytics and Stanford Sports
General Education Requirements
This seminar is expected to be in high demand. If you rank it as your first choice for priority enrollment, please be sure to apply for a second and third choice seminar for the quarter. You are also encouraged to write an additional statement for your lower ranked selection(s) so those faculty learn about your interest.
Course Description
Sophisticated data collection and analysis are now key to program success across many sports: Nearly all professional and national-level teams employ data scientists, and "datathletics" is becoming prevalent in college sports as well.
This immersive seminar combines extensive hands-on data analytics with a first-hand peek into Stanford athletics. Class meetings roughly alternate between: (1) instruction in a variety of tools and techniques for analyzing and visualizing data; and (2) guest lectures by Stanford athletics coaches explaining how data is or could be used in their sport. Through regular problem sets, students bring each week's tools to bear on data related to the week's sport.
One goal of the class is empowering students to perform compelling data analytics by mastering tools across a wide spectrum, including spreadsheets, the Tableau system for data preparation and visualization, Jupyter notebooks, relational databases and SQL, Python and many of its data-specific packages including Pandas, and machine learning.
On the sports side, while the Stanford coaches may touch on many aspects of data collection and analysis, the main focus of this course is on using data for strategic decision-making rather than optimizing individual human performance.
Meet the Instructor: Jennifer Widom
“I'm currently Dean of the School of Engineering, but I'm also a computer science professor whose research and teaching has always revolved around tools and techniques for managing and analyzing data. When I began my career in the 1990s, 'databases' was considered a dull topic whose impact was largely in business. (For the record: I never found it dull.) How things have changed! Now we 'data scientists' are top of the heap.
“I've taught courses about data ranging from two previous Introductory Seminars ('Big Data, Big Discoveries, Big Fallacies' and 'Working With Data: Delights and Doubts') to CS102 'Working with Data' that brought data science to hundreds of students across the university, to CS145 'Introduction to Databases' that served thousands of computer science majors, and a MOOC version of CS145 that's accumulated tens of thousands of finishers over 10+ years.
“Before earning my computer science PhD from Cornell I was a serious classical trumpet player, receiving my bachelor's degree from the Indiana University Jacobs School of Music. I'm the spouse of a professor, parent of two grown children, and an avid adventure-traveler, hiker, and scuba diver. During my 2016-17 sabbatical year I traveled the world delivering week-long data science short-courses in 20 developing countries on four continents, and I continue to bring data science to many corners of the globe whenever I find the chance.
“Relevant to this IntroSem, I serve as a faculty liaison for Stanford's Track & Field team and I look forward to meeting more coaches as we bring them to speak in our class.”
