A grant from the Data@Carolina initiative helped make this course possible. I was not shy about asking for help to develop STOR 390.

• Brendan Brown, Dylan Glotzer and Marshall Markham developed many of the (best) lectures
• Shankar Bhamidi supervised the development of this course

Many people provided input for this course

• Hadley Wickham (Chief Scientist at R Studio)
• Marshall Markham (Data Scientist at Maxpoint)
• Ian Murry (Lead Data scientist at Twitch)
• Elaine McVey (Lead Data Scientist at TransLoc)
• Ben Vigoda (CEO of Gamalon Machine Intelligence)
• Brian Gilman (VP Business Development at Gamalon Machine Intelligence)
• Cameron Freer (Logician and general purpose genius)
• Francis Tong (Data Scientist at Becton Dickinson)
• Bryan Davis (Data Analyst at Indeed.com)
• Rosie Scott (Data Analyst at Indeed.com)
• Zeydy Ortiz (Chief Data Scientist at DataCrunch Lab)
• Danielle Dean (Senior Data Scientist at Microsoft)
• Josh Jacobson (recovering programmer)
• Aaron Brubaker (SILS director of IT)
• Annie Henderson (Buisness Intelligence at Quid)
• Dominic Spadacene (no one really knows what Dom is up to these days…)
• Brendan Schneiderman (Senior Associate at E3)

• Abby Stevens (Data Engineer at Doximity)

• Jeff Leek (Professor of Statistics at Johns Hopkins)
• Mine Cetinkaya-Rundel (Professor of Statistics at Duke)
• Rafael Irizarry (Professor of Statistics at Harvard)
• Joe Blitzstein (Professor of Statistics at Harvard)
• Giles Hooker (Professor of Statistics at Cornell)
• Ryan Thornburg (Professor of Journalist at UNC)
• Steve Marron (Professor of Statistics at UNC)
• David Mimno (Professor of Information Science at Cornell)
• Diane Pozefsky (Professor of Computer Science at UNC)
• Jay Aikat (Professor of Computer Science at UNC)
• James Wilson (Professor of Statistics at USF)
• Abibail Panter (Senior Associate Dean for Undergraduate Education at UNC)
• Robin Cunningham (Professor of Statistics at UNC)

• Edward Carlstein (Professor of Statistics at UNC)

• Kelly Bodwin (Statistics PhD student at UNC)
• John Palowitch (Statistics PhD student at UNC)
• Jonathon Williams (Statistics PhD student at UNC)
• Jimmy Jin (Statistics PhD student at UNC)
• Eric Friedlander (Statistics PhD student at UNC)
• Kathryn Heal (Math PhD at Harvard)
• Arturo Fernandez (Statistics PhD student at Berkely)
• Jeffry Finkelstein (CS PhD student at BU)

• Walter Cai (CS PhD student at UW)

and of course my parents.

Much of the course content was inspired by other fantastic data science courses offered around the country.

• Coursera’s data science specialization by the Johns Hopkins guys
• STAT 545 at UBC by Jenny Bryan
• Intoduction to Data Analysis at Rice by Hadley Wickham
• CS 109 at Harvard by Joe Blitzstein

The course content drew on a number of other sources:

• Teaching and Learning STEM by Richard Felder and Rebecca Brent
• Trees, Maps and Theorems: Effective Communication for Rational Minds by Jean-luc Doumont
• R for Data Science by Garrett Grolemund and Hadley Wickham
• An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
• The Data Science Handbook
• Partially Derivative
• Simply Statistics

There were a number of wonderful guest speakers

• Marshall Markham
• Dan Yang
• Lucia Gjeltema
• Frances Tong
• Ryan Thornburg
• Quinn Underriner