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.
Minimum Units in the Program
Minimum University Units
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- 1056451
Most students should take CS 106A. However, students with prior programming experience in a language other than Python may instead take course. Note that course (required for major) uses Python.
Students with prior experience in Python who successfully complete course without taking CS 106A can have the CS 106A requirement waived.
Before taking Math 51, students will need to complete Math 19, 20, and 21 or AP Calculus. This may require up to 10 units of coursework in addition to the Data Science BS requirements.
- 1172571
OR 1172581
OR 2183491
Most students should take MATH51; MATH 61CM or MATH 61DM are available as more advanced alternatives.
- 2244902
- 1172891
OR 1172961
Most students should take MATH 104; MATH 113 is available as a more advanced alternative.
- 2254081
- 2012081
OR 1254211
Most students should take STATS 191; STATS 203 is available as a more advanced alternative.
- 1042771
OR 2253771
OR 2193641
OR 2066521
Most students should take one of the MS&E 111 courses; EE 364A is available as a more advanced alternative.
The Extended Core is specific to each version of the data science major (BS or BA) and offers additional coursework in the methods and frameworks used in each program's theoretical and applied areas of study.
- 1172591
OR 1172601
Most students should take MATH 52; MATH 62CM is available as a more advanced alternative.
- 2085321
OR 1056821 - 2226181
- 1172581
OR 1172601
OR 1172621 - 2183491
OR 2183501
OR 2183511 - 1172961
- 1173031
OR 1173491 - 2021882
The proof-writing course may double count with other requirements in the major.
- 1045431
- 1254311
- 2120991
- 2181541
- 2260352
- 2250151
- 1055861
- 2213951
- 2072331
Students who identify another course that explores the intersection between data, technology, and ethics may submit the data science requirement inquiry form to obtain approval from the Program Director.
- 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.
The capstone is a culminating experience completed during senior year. Students choose one of the following options. In addition, each student must participate in the final Capstone Showcase in spring of their senior year.
- 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 2275351
OR 2264311
OR 2261362
OR 2260941
DATASCI 120 double counts with the WIM requirement.
Completing DATASCI 120 and an independent research project in data science could also be considered for the capstone requirement; the project must be pre-approved by the program director.
By the final study list deadline of autumn quarter during senior year, students should join the Canvas page for Independent Research Projects.
During autumn quarter of senior year, students should find a professor who agrees to supervise the research project.
By the last day of classes of autumn quarter, students must complete the Proposal to Use Independent Research for Data Science B.S. Capstone form, have it approved by the research advisor, and submit it to the Canvas page for Independent Research Projects. Approval must be obtained from the program director through this process.
The students should enroll in course (independent study) for a letter grade with the supervising professor in every quarter until they finish conducting the research and creating the report/poster.
To complete the capstone, the student must submit a final report and approval form signed by their research advisor.
- 2237382
- 2244981
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
- 2174161
- 2258081
- 2258101
Students must complete one of the PWR 91 courses listed or a PWR194 course that is tagged for the specific notation (aside from PWR 91NSC, which is already required).
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- 2194421
- 2282751
See NSC Overview for specific approved courses.
An additional (3-5 unit) non-PWR elective course is required to complete the Notation in Science Communication.
This website lists sample courses that could qualify as non-PWR elective courses. Students must email notationsc@stanford.edu with their choice of elective course, whether that course is on this list or not, in order for that course to count toward their progress in the Notation. If you have questions about the non-PWR Elective course requirement, email notationsc@stanford.edu.
WIM courses may not double- count towards both the department and NSC requirements.
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 upper-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
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- 2226321
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- 2071961
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- 2193671
- 2193751
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OR 1172621
OR 2089871 - 1038991
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- 1237941
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- 2244702
- 2193741
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- 2133671
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An additional course from the “Machine Learning for Neuroscience” category above can also be taken as an advanced neuroscience elective.
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OR 1172621
OR 2183501
- 1056641
- 1056491
- 1056751
- 1056821
- 1056871
- 1254201
OR 2264341
OR 2264331
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.
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- 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
OR 2266401
- 1254251
- 1254321
- 2254172
- 2184891
- 2171371
- 2092251
- 2250931
- 1133661
- 1008851
- 1013241
- 1254521
- 1045511
OR 2045041
OR 1045921 - 2121101
- 2158531
- 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.
- 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.