CSE 519 - Data Science

Fall 2020

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.

  • Course Time: 9:45-11:05AM Tuesday and Thursday
    Place: Zoom (via Blackboard) The Zoom link is available on Piazza if you can't find it on Blackboard
  • Steven Skiena's office hours are 11:05M-12:35PM Tuesday-Thursday, via Zoom,and by appointment.
  • The course teaching assistants will be:
  • Videos and slides from my Fall 2016 lectures is available here. The video from Fall 2017 appears here , but the quality is not good. The best stuff should always be available at www.data-manual.com.
  • Sign up for the Piazza class discussion board at https://piazza.com/stonybrook/fall2020/cse519.
  • Syllabus
  • Lecture Schedule


We will use my book The Data Science Design Manual, Springer-Verlag, 2017.The associated website www.data-manual.com points to many resources, including lecture notes/videos, errata, a problem solution Wiki, and sample Python notebooks for generating figures from the book.

I will welcome feedback on the book. Please keep track of errata in the book send them to me, ideally in one batch at the end of the semester.

Homework Assignments

Lecture Notes

I will give about 25 formal lectures this semester. All classes will be filmed by Echo360 and made available on Blackboard.

Ritika Nevatia made lecture notes she took in class one year available to all interested students. You may check them out if you wish.

Old lecture notes are available from the previous offering in Fall 2014.

Semester Projects

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.

Recommended Readings

The field of data science is still emerging, but there are several books which it will be useful to read and consult:

Videos: The Quant Shop

The Quant Shop is a series of eight 30 minute programs on Data Science, which are a product of the Fall 2014 offering of this course. Watch them for inspiration at the Quant Shop Vimeo channel.

Related Links


Steven S. Skiena
251 New Computer Science Building
Department of Computer Science
Stony Brook University
Stony Brook, NY 11794-2424, USA