DATSC-BS - Data Science (BS)
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Program Overview
Mission of the Undergraduate Program in Data Science
The undergraduate program in Data Science aims to provide students with an analytical and quantitative foundation for tackling data-driven problems in science, industry, and society. Data science is an interdisciplinary field combining computational and inferential reasoning to extract knowledge or insights from data for use in various applications. It synthesizes the most relevant parts of foundational disciplines to solve particular problems or applications. As more data and new ways of analyzing data become available, our economy, society, and daily life will become even more dependent on our ability to learn from data systematically.
Students pursuing a BS in Data Science will acquire a core foundation of mathematics basic to all the mathematical sciences and be introduced to concepts and techniques of computation, optimal decision-making, probabilistic modeling, and statistical inference. Beyond this foundation, students can explore how inferential and computational thinking can be effective in areas as diverse as finance, biology, marketing, and engineering; or they can choose to acquire greater depth in one of our core disciplines. The BS in Data Science is an ideal major to prepare students for graduate study in quantitative fields, such as computer science and statistics, and for careers in various industries that require quantitative work, such as information technology and finance.
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 courses in each of these departments. Students are required to choose a subplan: The Mathematics and Computation subplan allows students to explore the core subjects further. In contrast, there are three other subplans available for students who are interested in data science's applications in one of the following areas: biology and medicine, computational neuroscience, or quantitative finance.
Preparing for the Major
Before declaring the major, students must complete two of the following courses and be enrolled in the third: Math 51, DATASCI 112, and STATS 117 or 118. Note that students can take CS 109/MS&E 120/EE 178 in place of STATS 117 to fulfill major requirements, but then they must take STATS 118 before declaring.
In addition, students must meet with a peer advisor, complete the program sheet, and meet with our student services team member. See the How to Declare page on our website for more information.
Minimum Units in the Program
Minimum University Units
Degree Requirements
- 1172571
OR 1172581
OR 2183491 - 1172591
OR 1172601
OR 2183511
- 2085321
- 1056821
- 2226181
- 1172581
- 2183491
- 1172601
- 2183501
- 1172621
- 2183511
- 1172961
- 1173031
- 2021881
- 1173491
The proof-writing course can double count with other requirements within the major.
- 1056441
OR 2212641 - 1056451
For the first requirement, most students should take CS 106A. However, students who have experience with programming but not Python can take CS 193Q instead. Note that DATASCI 112 (the required gateway course) uses Python.
For students with prior experience in Python who successfully complete DATASCI 112 without taking CS 106A, CS 106A can be waived.
- 2244902
We advise students to take STATS 117, STATS 118, and STATS 200. However, students may substitute CS 109, EE 178, or MS&E 120 in place of STATS 117. Alternatively, students can substitute MATH 151 in place of both STATS 117 and STATS 118.
- 2254081
- 2254091
- 1254161
OR 2271341
- 2085281
- 2254091
- 1254161
OR 2271341
- 1038311
- 2254091
- 1254161
OR 2271341
- 1045201
- 2254091
- 1254161
OR 2271341
- 1173351
- 1254161
OR 2271341
- 1045431
OR 1254311 - 2012081
OR 1254211
OR 1254801
- 1172891
OR 1172961 - 2066521
OR 1042771
OR 2253771
OR 2193641
Students will explore data science in practice by completing the ethics requirement along with the WIM and capstone.
Complete one course that explores the intersection between data, technology, and ethics.
- 2120991
- 2181541
- 2260352
- 2250151
- 1055861
- 2213951
- 2197651
- 2072331
Students who identify another course that explores the intersection between data, technology, and ethics may petition to have that course count toward this requirement, with permission from the Program Director.
At least three quarters before graduation, majors must meet with the Student Services Officer to confirm their plan for completing degree requirements.
All courses that fulfill major requirements must be taken for a letter grade, except courses offered satisfactory/no credit only.
Students may be granted a one-time exception to take a core course for credit (CR) -- except for STATS 117, STATS 118, STATS 200, and the capstone, which must be taken for a letter grade.
- 2237382
- 2253591
AND 2253501 - Hxh1qjyZ2tKYsR47qfHR
DATASCI 120, DATASCI 192A, DATASCI 192B, and DATASCI 199W double count with the capstone requirement. See capstone requirement for details.
- 2237382
- 2254191
DATASCI 120 double counts with the WIM requirement.
- 2253591
- 2253501
DATASCI 192A and DATASCI 192B double count for the capstone and WIM requirements.
- 2237382
- 2265491
OR 2264311
OR 2261362
OR 2260941
OR 2266612
DATASCI 120 double counts with the WIM requirement.
Completing DATASCI 120 and an independent research project in data science with a final report could also be considered for the capstone requirement. This project would need to be pre-approved by the program.
- 2237382
DATASCI 120 double counts with the WIM requirement.
- Hxh1qjyZ2tKYsR47qfHR
DATASCI 199W is available only to students in the Honors program, and it double counts with the WIM requirement.
Completing DATASCI 120 and the Notation in Science Communication will satisfy the capstone requirement. Note that students must fulfill all the requirements for the Notation in Science Communication in order to fulfill the capstone requirement.
- 2237382
- 2258081
- 2258101
Students must submit a Data Science Honors Proposal Form describing the concentration for honors work, including the courses they intend to use, by the final study list deadline two quarters before the expected degree conferral quarter. See our website for more information.
In addition to meeting all requirements for the BS, the student must:
Maintain a GPA of at least 3.5 in all major coursework.
Complete 15 units of graduate-level coursework. These 15 units must include at least 6 units of courses that involve substantial independent work, such as small group seminars, research-based courses, or independent reading/research courses (e.g., DATASCI 199).
Participate in the annual Data Science capstone showcase, where all students who have carried out independent work as part of their degree program (for example, in any of the capstone experiences) will share their learnings with posters, oral presentations, or other media.
Assemble a final portfolio showcasing the student’s ability to think independently and creatively using data science tools. Students will be provided specific instructions for the portfolio (including time for submission and guidelines). The portfolio will have two components:
(a) Final report of the independent work experience
(b) A self-reflection essay summarizing the learning achieved in the area of concentration
- 1056641
- 2226321
- 1056871
- 2071961
- 1272172
- 1410302
- 2159421
- 2193661
- 2193651
- 2193671
- 2193751
- 1115811
- 1115841
- 1115901
- 1172611
OR 1172621
OR 2089871 - 1038991
- 2261321
- 1119291
- 1237941
- 1240421
Note: The title and content of BIO 154 has changed since it was included as an option; while it would still technically be accepted, we would no longer recommend it to fulfill this requirement, as it is no longer an introductory neuroscience course.
- 1237921
- 1408383
- 2045911
- 2226491
- 2244702
- 2193741
- 2234572
- 2234582
- 2260941
- 2231661
- 2164871
- 1218071
- 2146121
- 2138421
- 2102451
- 2156871
- 2156561
- 2133671
- 2253951
- 2124482
- 2244551
An additional course from the “Machine Learning for Neuroscience” category above can also be taken as an advanced neuroscience elective.
- 1172611
OR 1172621
OR 2183501
The only course substitutions permitted in this subplan are technical electives, with advisor approval (see note).
- 1056641
- 1056491
- 1056751
- 1056821
- 1056871
- 1254201
OR 2264341
OR 2264331
OR 2150031
OR 2167441
OR 1254901 - 2235031
OR 2214431 - 2159451
Complete 2 additional technical electives from the list below for a total of at least 6 units. Each course must be at least 3 units. Students may use a maximum of one independent study/research course (3 units) as a technical elective if the research is related to data science and approved by the program director. See our website for recommended courses.
- 2243683
- 2115901
- 1295152
- 1406151
- 2092251
- 2041841
- 1133291
- 1133331
- 2250931
- 1133581
- 1133621
- 2250312
- 2020291
- 2260053
- 2184991
- 2172851
- 1045511
- 1222441
- 1222451
- 2173281
- 1248841
ECON 102A/B overlap significantly with other courses in the major and are not accepted.
POLISCI 150A/B overlap significantly with other courses in the major and are not accepted.
With approval from the program director, other courses may be used to fulfill part of the elective requirement. Courses must provide skills relevant to the Data Science degree and not overlap courses in the student's program. To initiate this process, please fill out the Elective Approval Form.
Examples of courses that would NOT count as electives because of significant overlap with other required major courses or content too far removed from Data Science are ECON 102A, ENGR 108, MS&E 120, and MS&E 140.
- 1132501
- 1254251
- 1254321
- 2254172
- 2184891
- 2171371
- 2092251
- 2250931
- 1008851
- 1013241
- 2208091
- 1254521
- 1045511
OR 2045041
OR 1045921 - 2121101
- 2158531
- 2250021
- 2245031
- 2184891
Complete 1 additional technical elective from the list below. Each course must be at least 3 units. Students may use a maximum of one independent study/research course (3 units) as a technical elective if the research is related to data science and approved by the program director. See our website for recommended courses.
Complete at least 1 course from one of the following course sets, or at least 1 course from the list of pre-approved electives below.
- 2243683
- 2115901
- 1295152
- 1406151
- 2092251
- 2041841
- 1133291
- 1133331
- 2250931
- 1133581
- 1133621
- 2250312
- 2020291
- 2260053
- 2184991
- 2172851
- 1045511
- 1222441
- 1222451
- 2173281
- 1248841
ECON 102A/B overlap significantly with other courses in the major and are not accepted.
POLISCI 150A/B overlap significantly with other courses in the major and are not accepted.
With approval from the program director, other courses may be used to fulfill part of the elective requirement. Courses must provide skills relevant to the Data Science degree and not overlap courses in the student's program. To initiate this process, please fill out the Data Science Requirement Inquiry form.
Examples of courses that would NOT count as electives because of significant overlap with other required major courses or content too far removed from Data Science are ECON 102A, ENGR 108, MS&E 120, and MS&E 140.