The information and requirements found below apply to the current academic catalog. For other catalog years, please consult the archive.
Data Science Major / Stats and Data Science Major
The Department of Mathematics offers a Bachelor of Arts (B.A.) in Statistics & Data Science (SDS), and a Bachelor of Science (B.S.) in Data Science (DS).
In general, B.A. degrees require more second language proficiency (fourth semester proficiency, compared to second semester proficiency for a B.S.), while B.S. degrees are more science intensive (our B.S. requires two lab science classes, in addition to fulfillment of the Exploring Perspectives: Natural Scientist requirement included in the General Education program).
The new DS major requires more units overall than the SDS major (51 vs 34, minimum), providing more depth while the SDS major provides more breadth. A minor is required for the SDS major, but optional for the DS major.
For information on selecting the appropriate program and courses to prepare for various types of graduate programs, please speak with an advisor.
Please be sure to read through all applicable degree policies before declaring a major.
Degree Requirements
Bachelor of Arts in Statistics & Data Science
The Bachelor of Arts in Statistics & Data Science (SDS) provides a solid foundation in mathematics, statistics, data science, and computer programming. Students pursuing the B.A. in SDS also have a broad range of elective options to choose from outside of the core degree curriculum.
A minor in any subject outside the math department is required with this major.
For a more detailed layout of requirements or a list of changes to the degree requirements from year to year, please see the requirements knowledgebase.
Bachelor of Science in Data Science
Offered through the Department of Mathematics, the B.S. in Data Science combines a strong foundation in mathematics, statistics, data science, and computing. The emphasis courses provide students with a deeper understanding of how data science principles and techniques apply within their chosen area of focus. Students engage with complex data and applied projects throughout the curriculum, gaining the skills needed to drive innovation and discovery in science, technology, and AI.
A minor is optional with this major.
For a more detailed layout of requirements or a list of changes to the degree requirements from year to year, please see the requirements knowledgebase.
Statistics & Data Science B.A.
The B.A. in Statistics & Data Science (SDS) has been revised for the 2025-26 academic year. Some of the new features:
- MATH 223 (Vector Calculus), MATH 464 (Theory of Probability), and MATH 466 (Theory of Statistics) are now electives instead of required courses
- MATH 263 has been added to the core courses, providing students with earlier exposure to statistics in the major
- Students now select three electives (at least two of which are upper-division) instead of just one. Elective options have also been expanded to include courses from other departments, some of which may also count as Gen Eds.*
A minor is still required with this major, and minor courses may not overlap with the courses used to fulfill major requirements.
*Up to 3 courses may count to fulfill General Education Exploring Perspectives or Building Connections requirements as well as major, pre-major, minor, and/or certificate requirements.
The complete official requirements for the major are given in the University Catalog in the form of an Academic Advisement Report (ADVIP), as seen below. It is important for students to consult with their academic advisor about their choice and order of courses, as well as which additional courses would strengthen their degree program.
SDS Supporting Computing Requirements
Python, SQL, and R are all essential skills for any Data Scientist. Statistics & Data Science Majors take a Python course early in the major, followed by a SQL course. With these foundational programming skills, students are prepared to learn R as part of the DATA 363 course.
Choose one course:(*)
(*)Either CSC 110 or ISTA 130 is recommended for most students; CSC 120 or CSC 250 will also satisfy the requirement if available. As an alternative, qualified students may complete both (ECE 101 or ECE 175) AND either BE 205 or CHEE 205 or AME 209). Contact the Math Center if you need any of these alternative courses pulled into your advisement report.
SDS Core Courses
The following core courses are required for all students selecting the B.A. in Statistics & Data Science (SDS).
- MATH 122A AND MATH 122B (1) or MATH 125— Calculus I
- MATH 129— Calculus II
- DATA 201 — Foundations of Data Science
- MATH 263 — Introduction to Statistics and Biostatistics
- MATH 313 — Introduction to Linear Algebra
- DATA 363— Introduction to Statistical Methods
- DATA 375— Introduction to Statistical Computing
- DATA 467 — Applied Linear Models
- DATA 474— Introduction to Statistical Machine Learning
- DATA 498A — Capstone for Statistics and Data Science
SDS Elective Courses
The B.A. in Statistics & Data Science requires three major elective courses, at least two of which must be upper-division (numbered 300 or above). Choose from the list below.
- DATA 367— Statistical Methods in Sports Analytics
- DATA 396T— Topics in Undergraduate Statistics & Data Science
- DATA 412 — Linear Algebra for Data Science
- DATA 439 — Statistical Natural Language Processing
- DATA 462— Financial Math
- DATA 468— Applied Stochastic Processes
- DATA 496T— Advanced Topics in Undergraduate Statistics & Data Science
- DATA 498H — Honors Thesis
- GEOG 457 — Statistical Techniques in Geography, Regional Development and Planning
- INFO 402— Data Ethics
- ISTA 320— Applied Data Visualization
- ISTA 321— Data Mining and Discovery
- ISTA 410— Bayesian Modeling and Inference
- MATH 223— Vector Calculus
- MATH 464— Theory of Probability
- MATH 466— Theory of Statistics
- PHIL 206 — Ethics of Artificial Intelligence
- PHIL 346 — Minds, Brains and Computers
- PHIL 455 — Philosophy and Artificial Intelligence
- SIE 440— Survey of Optimization Methods
- WFSC 223 — Dealing With Data in the Wild
DS Core Courses
The following core courses are required for all students selecting the B.S. in Data Science (DS).
- Choose one:
- Choose one:*
- MATH 122A AND MATH 122B or MATH 125 — Calculus I
- MATH 129 — Calculus II
- DATA 201 — Foundations of Data Science
- MATH 263 — Introduction to Statistics and Biostatistics
- MATH 313 — Introduction to Linear Algebra
*ISTA 131 will not substitute for CSC 120 as a prerequisite to future CSC courses for students selecting the Computing emphasis.
DS Emphasis Options
All Data Science (DS) majors must declare and complete one of the following emphases. Each emphasis requires at least 31 units of course work; the number of upper-division units required varies by emphasis.
A minor is optional for the DS major.
The complete official requirements for each emphasis are given in the University Catalog in the form of an Academic Advisement Report (ADVIP), as seen below. It is important for students to consult with their academic advisor about their choice and order of courses, as well as which additional courses would strengthen their degree program.
Applied Statistics
The emphasis in Applied Statistics is intended primarily for students wanting a more statistical-focused data science major in preparation for entering the workforce after graduation. This emphasis may also be appropriate preparation for graduate study in fields that rely heavily on statistics and data science.
Comprehensive Statistics
The emphasis in Comprehensive Statistics is intended for students planning to attend graduate school in statistics or statistics & data science.
Computing
The emphasis in Computing is intended for students who want to learn more about the computational side of data science.
Molecular and Cellular Biology
The emphasis in Molecular and Cellular Biology is intended for students who are interested in applying data science methods to biology.
