This concentration in data science is intended for COMPSCI majors interested in studying data science in depth, with a distinctively computational focus. If you are interested in data science but not necessarily in becoming a COMPSCI major, there are other options that are less concerned with the lowerlevel computational aspects:
 The IDM (interdepartmental major) in Stat+CS on Data Science covers more topics on statistical data analysis, while
 The IDM in Math+CS on Data Science focuses more on the mathematical foundations of data science.
Prerequisites
 One of the following introductory COMPSCI courses or equivalent:
 COMPSCI 101L (Introduction to Computer Science)
 COMPSCI 102 (Interdisciplinary Introduction to Computer Science)
 COMPSCI 116 (Foundations of Data Science)
 MATH 111L (Introductory Calculus I) or equivalent
 MATH 112L (Introductory Calculus II) or equivalent
 Probability: STA 230, STA 231, STA 240
Requirements
 COMPSCI 201 (Data Structures and Algorithms)
 COMPSCI 230 (Discrete Math for Computer Science) see substitutions
 COMPSCI 250 (Computer Architecture)
 COMPSCI 316 (Introduction to Databases) or 516 (Database Systems)
 COMPSCI 330 (Design & Analysis of Algorithms)
 Two courses in MATH/STA:
 Linear Algebra: MATH 218 or MATH 221
 Statistics: STA 250*, STA 360**, STA 432, or MATH 342
 *ECE 450 is an approved substitution for STA 250
 **You cannot use STA 360 as an elective if you are using it as the requirement here.
 COMPSCI 216 (Everything Data)
 One of the following courses:
 COMPSCI 371 (Elements of Machine Learning)
 COMPSCI 370* (Intro. Artificial Intelligence)
 COMPSCI 570 (Artificial Intelligence)
 COMPSCI 571 (Probabilistic Machine Learning)
 COMPSCI 671* (Machine Learning)
 *Note: 370 was renumbered from 270 in Fall 2019, and 671 from 571 in Spring 2019.
 Three Electives at 200level or higher. One out of the three electives must be a COMPSCI course.
 Two additional courses must be drawn from either the above list (COMPSCI 370, 371, 570, 571, 671) or the list below.
 STA 325 (Machine Learning and Data Mining)
 STA 360 (Bayesian Inference)  You cannot count STA 360 as an elective if you are using it for the Stats requirement above
 COMPSCI 260 (Computational Genomics)
 COMPSCI 290 (Algorithms in the Real World)
 COMPSCI 474 (Data Science Competition)
 COMPSCI 527 (Computer Vision)
 COMPSCI 590 (Topics) on following subjects (some may not be offered regularly):
 Reinforcement Learning
 Algorithmic Foundations of Data Science
 Focus on SARSCov2 and COVID19 (CBB 590.01)  Spring 2021

One additional elective (independent Study possible) in COMPSCI, MATH, STA, or a related area approved by the Director of Undergraduate Studies.
 Two additional courses must be drawn from either the above list (COMPSCI 370, 371, 570, 571, 671) or the list below.