The Data Science Program Overview
This common program structure between the three major offerings was established in AY 2026-27. If you declared the minor prior to September 1, 2026, see how your major requirements are structured via our past requirements page.
The Data Science Core
The Data Science Core establishes the foundational skills and mathematical mindset required of a data scientist. Every student in the Program in Data Science completes the same core, whether pursuing the B.S. in Data Science, the B.A. in Data Science & Social Systems, or the B.A. in Data Science for Artistic and Cultural Analysis.
The Data Science program is interdisciplinary in its focus, and sponsored by Stanford’s departments of Statistics, Mathematics, Computer Science, and Management Science & Engineering. Students are required to take core courses in each of these departments.
Core Courses
MATH
Linear Algebra, Multivariable Calculus and Modern Applications
DATA
Principles of Data Science
PROBABILITY
Introduction to Probability Theory
MATHEMATICAL MODELING
Applied Matrix Theory
STATISTICS
Introduction to Applied Statistics
OPTIMIZATION
Introduction to Optimization (Standard, Data Science or Accelerated)
The core sequence above is the recommended path for most majors, but the program allows for flexibility. See the alternative course options.
Advanced Alternatives & Approved Substitutions
Students interested in more advanced alternatives to the standard courses may choose from the following. Students may take any number of advanced alternatives:
| required Course | Advanced Alternatives |
|---|---|
| MATH 51 | MATH 61CM, MATH 61DM |
| MATH 104 | MATH 113 |
| STATS 191 | STATS 203 |
| MS&E 111, 111DS or 111X | EE 364A |
Students in the B.A. programs may use up to two of the following pre-approved substitutions within the Data Science Core without additional approval. Students requesting more than two substitutions must submit the inquiry form and obtain approval from the program director.
| REQUIRED COURSE | B.A. APPROVED SUBSTITUTIONS (limit two) |
|---|---|
| MATH 104 | ENGR 108 |
| STATS 117 | CS 109, MS&E 120, or EE 178 |
| STATS 191 | MS&E 125 or MS&E 226 |
Beyond the Core
Students build on the Data Science core through an Extended Core, a Concentration, and the Data Science in Practice capstone. These requirements vary across the three majors, allowing students to pursue their interests while developing the methodological depth and substantive knowledge their work will demand.
Components of the Data Science Majors
Data Science Core
8 courses
Foundational knowledge in mathematics, computation and statistics
Extended Core
4-5 courses
Additional methods and frameworks relevant to the major
Concentration
4-8 courses
Concentrated study in an area of interest
Data Science In Practice
Capstone and WIM requirements
Component | Data Science | Data Science & Social Systems | Data Science for Artistic & Cultural Analysis |
|---|---|---|---|
Extended Core
| One course in each:
| One course in each:
| One course in each:
|
Concentrations
| Choose one subplan:
| Choose one pathway:
| Choose one pathway:
|
| Data Science in Practice |
|
|
|
| Learn More | Data Science Requirements | Data Science and Social Systems Requirements | Data Science for Artistic and Cultural Analysis Requirements |
Data Science Program Minors
Our program offers a minor in Data Science and a minor in Statistics. Both complement majors in the natural sciences, social sciences, and humanities. Each minor consists of six courses, with the Data Science minor emphasizing practical skills in data analytic methods and the Statistics minor emphasizing foundational knowledge in probability and statistics.
Data Science Minor Requirements Statistics Minor Requirements