Faculty
DeJuran Richardson
Ernest H Volwiler Professor of Mathematics
Chair of Mathematics and Computer Science
Sugata Banerji
Associate Professor of Computer Science
Arthur Bousquet
Associate Professor of Mathematics
Andrew Gard
Assistant Professor of Mathematics
Sara Jamshidi
Assistant Professor of Computer Science and Mathematics
Craig Knuckles
Professor of Mathematics and Computer Science
Enrique Trevino
Associate Professor of Mathematics and Computer Science
Chair of Mathematics and Computer Science
Required courses at the 200-level or higher may count towards the major or minor in data science, mathematics and computer science only if the grade earned in the class is “C-” or better and may be taken Pass-NoPass, as long as the grade originally earned in the class is “C-” or better. Required courses at the 100-level have no minimum grade requirement and may be taken Pass-NoPass.
Requirements for the Major in Data Science:
At least 10 credits, including the “core” plus one “track”
The Core (6 Courses)
- Mathematics 110: Calculus I
- Computer Science 112: Computer Science I
- One course chosen from the following:
- Mathematics 150: Introduction to Probability & Statistics
- Economics/Business/Finance 130: Applied Statistics
- Psychology 222: Research Methods & Statistics II
- Mathematics 231: Linear Algebra OR Mathematics 240: Introduction to Computational Mathematics
- Mathematics 250: Introduction to Statistical Programming
- Computer Science 250: Programming for Data Applications
Option I – The Finance and Economics Track (5 courses unique courses with 2.5 prerequisites) Only available for students admitted prior to fall 2024.
- Economics 110: Principles of Economics
- Finance 210: Financial Management
- Business 230: Financial Accounting
- Economics 330: Econometrics (COLL 150 & ECON 210 prerequisite requirement)
- Finance 485: Quantitative Finance (Senior Studies requirement; FIN 320 prerequisite requirement)
Option II – The Statistics Track (5 courses)
- Mathematics 111: Calculus II
- Mathematics 210: Multivariable Calculus
- Mathematics 230: Abstract and Discrete Mathematics
- Mathematics 350: Mathematical Probability
- Mathematics 450: Mathematical Statistics (Senior Studies requirement)
Option III – The Computer Science Track (4 courses)
- Computer Science 212: Computer Science II
- Computer Science 317: Data Structures and Algorithms or Computer Science 325: Artificial Intelligence
- Computer Science 327: Introduction to Database Systems
- Computer Science 450: Computer Vision & Machine Learning (Senior Studies requirement)
Requirements for the Minor in Data Science:
At least 6 credits
The minimum requirement for the Data Science Minor is to complete the (6) courses listed as “The Core” requirements for the major.
Learning Outcomes
The expected Student Learning Outcomes for the Data Science Department are:
1. Effectively use statistics, computing technology, and computational methods to summarize and analyze various types of data.
2. Communicate the rationale and results of their data analytic work in a clear and effective manner.