Required credits: 71-72
Core Courses (53 credits)
M 144 - Calculus I 4 credit(s) *
M 145 - Calculus II 4 credit(s)
M 220 - Linear Algebra and Matrix Theory 3 credit(s)
M 240 - Calculus of Several Variables 4 credit(s)
M 260 - Introduction to Data Science 3 credit(s)
M 360 - Probability Theory 3 credit(s)
M 362 - Elements of Statistics 3 credit(s)
CS 114 - Fundamentals of Computing I 4 credit(s) *
CS 115 - Fundamentals of Computing II 4 credit(s)
CS 220P - Data Structures 3 credit(s)
EC 110 - Principles of Macroeconomics 3 credit(s) *
DS 330 - Data Visualization 3 credit(s)
DS 385W - Capstone in Data Science I 3 credit(s)
DS 485W - Capstone in Data Science II 3 credit(s)
DES 200 - Introduction to User Interface Design 3 credit(s)
UISS 340D - Ethics in the Professions 3 credit(s) *
Track Courses
CS/Math Track (19 credits)
M 221W - Discrete Mathematics I 4 credit(s)
M 368 - Predictive Modeling for Data Science 3 credit(s)
CS 342 - Algorithms and Complexity 3 credit(s)
CS 351 - Introduction to Artificial Intelligence 3 credit(s)
CS 365 - Principles of Database Systems 3 credit(s)
CS 368 - Data Mining 3 credit(s)
Business Track (18 credits)
AC 210 - Financial Accounting 3 credit(s)
EC 211 - Principles of Microeconomics 3 credit(s)
FIN 310 - Business Finance 3 credit(s)
QNT 350 - Introduction to Business Analytics 3 credit(s)
QNT 430 - Predictive and Business Analytics 3 credit(s)
QNT 450 - Business Data Mining 3 credit(s)