^{Data Analytics}
_{Curriculum}
All students are required to complete a core curriculum consisting of 54 credits in mathematics, computer science, data science, statistics, and philosophy bracketed by introductory and capstone courses designed for the degree.
Coursework required for all tracks
Lower Division

 CPTS/STAT 115: Introduction to Data Analytics
 Math 171: Calculus I
 Choose one of the following
 MATH 172: Calculus II
 MATH 182: Honors Calculus II
 MATH 220: Introductory Linear Algebra
 Choose one of the following
 CPTS 131: Program Design & Develop.Java
 CPTS 121: Program Design & Develop.C/++
 Choose one of the following
 CPTS 132: Data Structures –Java
 CPTS 122: Data Structures C/++
 CPTS 215: Data Analytics Systems & Algorithms
Upper Division
 CPTS 315: Introduction to Data Mining
 CPTS 451: Introduction to Database Systems
 CPTS 415: Big Data
 STAT 360: Probability & Statistics
 STAT 380: Decision Making & Statistics
 STAT 437: Statistical Analytics and Learning. (Prereq of Stat 435.)
 Choose one of the following
 STAT 412: Statistical Methods in Research I
 STAT 435(M): Statistical Modeling for Data Analytics. (Highly suggested – Prereq of Stat 360.)
 EconS 311: Introductory Econometrics (required for economics track)
 STAT 419: Intro to Multivariate Stats
 PHIL 450: Data Analytics Ethics
 CPTS/STAT 424 (CAPS): Data Analytics Capstone