Foundational Component (12 required courses)

• CS 151 - Computer Science through Programming
• CS 295 - Discrete Structures or
• MA 295 - Discrete Structures or
• MA 395 - Discrete Methods
• DS 303 - Discovering Information in Data
• DS 496 - Ethical Data Science Capstone
• IS 251 - Data Analytics and Information Systems or
• BH 251 - Data Analytics and Information Systems *
• IS 353 - Data Management and Database Systems or
• CS 485 - Database Management Systems
• IS 358 - Business Intelligence and Data Mining
• MA 251 - Calculus I
• ST 210 - Introduction to Statistics or
• ST 265 - Biostatistics or
• EC 220 - Business Statistics
• ST 310 - Statistical Computing
• ST 465 - Experimental Research Methods
• ST 472 - Applied Multivariate Analysis

•  

  * Restricted to Sellinger Scholars.

Elective Component

Choose three courses from the following:

• CS 312 - Object-Oriented Software Design
• CS 484 - Artificial Intelligence
• CS 487 - Big Data
• EC 420 - Econometrics
• EC 425 - Applied Economic Forecasting
• IS 453 - Information Systems Analysis and Design
• IS 460 - Data Visualization
• IS 465 - Text Mining
• MA 301 - Introduction to Linear Algebra
• ST 461 - Elements of Statistical Theory I: Distributions
• ST 466 - Experimental Design
• Or appropriate course as approved by program director

Freshman Year

Sophomore Year

Junior Year

Senior Year

Notes:

1. EC 102  and EC 103  are recommended to fulfill the Social Science Core.
2. MA 151  may be substituted for MA 251  with permission of the program director.
3. CS 212  is a prerequisite for CS 312 . MA 252  is a prerequisite for MA 301 . MA 351  is a prerequisite for ST 461 .
4. Up to two graduate-level Data Science courses may be taken as a DS Elective with approval from the program director.
5. CS 485 , ST 465 , and ST 472  are offered every other year.