School of Data Science and Society
Introduction
The School of Data Science and Society (SDSS) was founded in 2022 with a mission to serve the state, the nation, and the world with premier data science educational programs and unique, collaborative research programs directed to advance the public good. SDSS seeks to shape the emerging field of data science with a human-centric approach to the entire data life cycle and envisions a world made healthy, safe, and prosperous through data-informed decisions. The school offers learner-focused programs that develop core competencies in data science, preparing students for the workforce or an advanced degree program.
Admission to the Major
Those wishing to declare the Bachelor of Science (B.S.) in Data Science must be admitted to the School of Data Science and Society. Students are eligible to apply in the spring semester after completing or while currently enrolled in the prerequisite courses. Please see the school's website for the most up-to-date information about the admission to the major process.
Advising
After admission and acceptance, the Bachelor of Science in Data Science becomes a student's major. In addition to general advising through UNC Advising, students will receive academic and faculty advisors in the School of Data Science and Society. The School of Data Science and Society Academic Affairs Office manages additional student support services, including community-building activities and career preparation.
Preparing for the Bachelor of Science in Data Science
A student admitted to the School of Data Science and Society typically begins the Undergraduate Bachelor of Science in Data Science program in the spring semester of the second year or fall semester of the third year. First- and second-year students in the General College who consider themselves pre-data science B.S. majors complete certain prerequisite courses as part of their General Education requirements.
A pre-data science track includes successful completion (defined as earning a final grade of at least a C, not C-) of the following courses (or their equivalents):
| Code | Title | Hours |
|---|---|---|
| DATA 110 | 
Introduction to Data Science H | 3 |
| One of the following: | ||
|
Foundations of Statistics and Data Science H, F | ||
|
Introduction to Programming H | ||
| Introduction to Scientific Programming | ||
| MATH 231 |
Calculus of Functions of One Variable I H, F | 4 |
| MATH 232 |
Calculus of Functions of One Variable II H, F | 4 |
| MATH 233 |
Calculus of Functions of Several Variables H, F | 4 |
| or MATH 235 |
Mathematics for Data Science | |
| MATH 347 |
Linear Algebra for Applications F | 3 |
| One of the following: | ||
|
Discrete Mathematics for Data Science | ||
|
Discrete Structures H | ||
| Discrete Mathematics H | ||
| H | Honors version available. An honors course fulfills the same requirements as the nonhonors version of that course. Enrollment and GPA restrictions may apply. |
| F | FY-Launch class sections may be available. A FY-Launch section fulfills the same requirements as a standard section of that course, but also fulfills the FY-SEMINAR/FY-LAUNCH First-Year Foundations requirement. Students can search for FY-Launch sections in ConnectCarolina using the FY-LAUNCH attribute. |
Professors
Stan Ahalt, David Adalsteinsson, Amarjit Budhiraja, Melissa Haendel, Ashok Krishnamurthy, Terry Magnuson, Steve Marron, Jack Snoeyink.
Associate Professors
Wei-Tong (Louis) Fan, Sun-Ha Hong, Hsun-Ta Hsu, Youzuo Lin, Yifei Lou, Santiago Olivella, Courtney Rivard, Keriayn Smith.
Assistant Professors
Iain Carmichael, Can Chen, Anita Crescenzi, Neil Gaikwad, Dan Kessler, Lauren Kucirka, Harlin Lee, Alex McAvoy, Lina Montoya, Justin Sola, Huaxiu Yao, Ran Zhang, Weitong Zhang, Chudi Zhong, Tarek Zikry.
Teaching Professors
Richard Marks, Julie McMurry, Rei Sanchez-Arias, David Yokum.
