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 lower-level 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 216 - Everything Data
- COMPSCI 230 - Discrete Math for Computer Science or 232 (Discrete Mathematics and Proofs) see substitutions
- COMPSCI 210D - Introduction to Computer Systems or COMPSCI 250D - Computer Architecture
- COMPSCI 316 - Introduction to Databases or COMPSCI 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 480 is an approved substitution for STA 250 [NOTE: As of Fall 2020, STA 250 is no longer offered.]
- **You cannot use STA 360 as an elective if you are using it as the requirement here.
- One of the following courses:
- COMPSCI 370* - Intro. Artificial Intelligence
- COMPSCI 371 - Elements of Machine Learning
- 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 200-level or higher. One out of the three electives must be a COMPSCI course.
- One 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.
- 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 226 - User Research Methods in Human-Centered Computing
- COMPSCI 260 - Computational Genomics
- COMPSCI 321/521 - Graph-Matrix Analysis
- COMPSCI 333 - Algorithms in the Real World
- COMPSCI 390 (Special Topics) on the following subjects (some may not be offered regularly):
- Computational Approaches to Language Processing (Spring 2023)
- COMPSCI 445/MATH 465 - Intro to High Dimensional Data Analysis
- COMPSCI 474 - Data Science Competition
- COMPSCI 526 - Data Science
- COMPSCI 527 - Computer Vision
- COMPSCI 590 (Topics) on the following subjects (some may not be offered regularly):
- Reinforcement Learning
- Algorithmic Foundations of Data Science
- Focus on SARS-Cov-2 and COVID-19 cross-list CBB 590-01 - (Spring 2021)
- Causality and Fairness for Data Analysis (Spring 2023)
- Data Science Concepts and Applications (Spring 2023)
- Elements of Deep Learning (Spring 2023)