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Data Science

[ graduate program | faculty | courses ]

All courses, faculty listings, and curricular and degree requirements described herein are subject to change or deletion without notice.

Program Focus

Data science is concerned with drawing useful and valid conclusions from data. Data scientists develop mathematical models, computational methods, and tools for exploring, analyzing, and making predictions from data. They ask appropriate questions about data and interpret the predictions based on their expertise of the subject domain.

Two majors are offered (data science and business data science), as well as a minor in data science. Please note that students majoring or minoring in any of the computer science engineering programs (CSE-BS-001/ECE-BS-001, CSE-BS-002, CSE-BS-003, CSE-BS-004, CSE MN-001) may not double major or minor in data science or business data science. Additionally, students may not double major in data science and business data science or combine business data science with a minor in business (RSM-MN-002) or data science (DSC-MN-001), and data science majors may not minor in data science (DSC-MN-001).

The Data Science Major (DSC-BS-001)

The primary goal for the data science major is to train a generation of students who are equally versed in predictive modeling, data analysis, and computational techniques. To this end, in addition to learning about data science models and methods, students will acquire expertise in a particular subject domain. The major also educates students about the societal and ethical impact of data science so that they can make responsible decisions as data science practitioners. The program offers both a major and a minor in data science.

The major consists of 112 units, with fifty-two units from lower-division courses and sixty units from upper-division courses. The lower-division curriculum includes calculus and linear algebra courses for sixteen units, data science courses for twenty-eight units, and subject domain courses for eight units. The program includes twenty units of elective courses that will enable students to embark upon an in-depth exploration of one or more areas in which data science can profitably be applied. Alternatively, students can choose to explore the mathematical, statistical, and computational foundations of data science in even greater depth.

All majors will be required to undertake a senior project that will give them an opportunity to creatively synthesize much of what they have learned in the data science courses for addressing problems in chosen domains.

Lower Division

Students are expected to complete the following fifty-two units by the end of their sophomore year. All courses must be taken for a letter grade and passed with a minimum grade of C–.

  • Data Science (twenty-eight units):
    • COGS 9
    • DSC 10/R
    • DSC 20/R
    • DSC 30/R
    • DSC 40A/R
    • DSC 40B/R
    • DSC 80/R
  • Mathematics (sixteen units):
    • MATH 18 or MATH 31AH
    • MATH 20A
    • MATH 20B
    • MATH 20C or MATH 31BH
  • Subject Domain Courses: Students must choose one of the following two-course sequences (eight units)
    • Business Analytics and Econometrics: ECON 1 and ECON 3
    • Machine Learning and Artificial Intelligence: COGS 14A and COGS 14B
    • Science: BILD 1 and BILD 3
    • Social Sciences I: (POLI 5 or POLI 5D or ECON 5) or (POLI 30 or POLI 30D)
    • Social Sciences II: SOCI 60 and USP 4

Upper Division

Students must complete sixty upper-division units. All courses must be taken for a letter grade unless offered Pass/Not Pass only. A minimum grade of C– is required.

  • Core Courses (thirty-two units):
    • ECON 120A or MATH 183 or MATH 181A
    • MATH 189 or DSC 152
    • DSC 100
    • DSC 102
    • DSC 106
    • DSC 140A or CSE 150A
    • DSC 140B or CSE 151A
    • DSC 148 or CSE 158 or CSE 158R
  • Senior Project (eight units):
    • DSC 180A
    • DSC 180B
  • Electives (twenty units):
    • Any upper-division data science course not used to fulfill other requirements with the exception of DSC 197, 198, and 199.
    • Any of the following: BICD 100 and BIEB 174; COGS 108, 109, 118C-D, 120 (cross-listed with CSE 170), 121, 180, 181, and 189; COMM 106I, CSE 106, 151B, 152A, 152B, 156, 166, 170 (cross-listed with COGS 120), and 180; ECON 120B-C; ESYS 103 (cross-listed with MAE 124); LIGN 167; MAE 124 (cross-listed with ESYS 103); MATH 152, 173A-B, 180A-B-C, 181A-B-C-D-E-F, and 194; MGT 103 and 153; PHIL 174; POLI 117 (cross-listed with SIO 109), 170A, 171, 172, and 173; PSYC 106; SIO 109 (cross-listed with POLI 117) and 132; SOCI 102, 103M, 108, 109, 109M, 136, 165, and 171; USP 122, 125, 138, 153, 172, 175, and 180.
    • Students may petition to satisfy up to eight elective units using upper-division courses not on the list above but in their subject domain.
    • Students will be expected to fulfill all prerequisites for all courses, which may entail additional course work beyond the data science major requirements.

The Business Data Science Major (DSC-BS-002)

The goal of the business data science major is to prepare students for data-driven decision-making roles by integrating rigorous training in data science with foundational and applied knowledge of business functions—equipping graduates with the technical, analytical, and strategic skills needed to solve complex business problems and lead in data-centric industries.

The major consists of ninety-six units, with forty units from lower-division courses and fifty-six units from upper-division courses. The lower-division curriculum includes calculus and linear algebra courses for sixteen units, data science courses for sixteen units, and subject domain courses for eight units. The program includes sixteen units of elective courses that enable students to explore both data science applications and business topics, with an emphasis on strong empirical content.

All majors will be required to undertake a one-quarter capstone project that will give them an opportunity to creatively synthesize much of what they have learned in the data science and management courses for addressing problems in chosen domains. Although only specific prerequisites are required for the capstone, to get the most out of the experience, students are strongly encouraged to complete the majority of their course work for the business data science major prior to enrolling. Students will benefit most if they have completed as many core and elective courses as possible. It is recommended that students take this course as near as possible to graduation, when they will be best equipped to handle a significant empirical challenge.

Lower-division transfer credits for courses that are clearly equivalent in scope and content to lower-division courses required for this major will be accepted from regionally accredited U.S. institutions and from foreign institutions recognized by the Halıcıoğlu Data Science Institute (HDSI) and/or Rady School of Management.

Lower Division

All courses must be taken for a letter grade and passed with a minimum grade of C–.

  • Data Science (sixteen units):
    • DSC 10
    • DSC 20
    • DSC 40A
    • DSC 80
  • Mathematics (sixteen units):
    • MATH 18 or MATH 31AH
    • MATH 20A
    • MATH 20B
    • MATH 20C or MATH 31BH
  • Subject Domain Courses (eight units):
    • DSC 31
    • MGT 45

Upper Division

Students must complete fifty-six upper-division units. All courses must be taken for a letter grade unless offered Pass/Not Pass only. A minimum grade of C– is required.

  • Core Courses (thirty-six units):
    • MATH 183
    • DSC 100
    • DSC 140A
    • DSC 148 or MATH 189
    • MGT 100
    • MGT 127/127R
    • MGT 160
    • MGT 168
    • MGT 180/180R
  • Senior Project (four units):
    • DSC 181/MGT 191
  • Electives (sixteen units):
    • Two UD DSC courses: Any other DSC course numbered 100–170 or DSC 190.
    • Two UD MGT courses from list below:
      • MGT 104
      • MGT 108R
      • MGT 112
      • MGT 120
      • MGT 137
      • MGT 153
      • MGT 155
      • MGT 159T
      • MGT 162/162R
      • MGT 171/171R
      • MGT 172/172R
      • MGT 175
      • MGT 186
      • MGT 188
    • Students will be expected to fulfill all prerequisites for all courses, which may entail additional course work beyond the data science major requirements.

Minor in Data Science

This minor is intended for students whose primary area of interest lies outside data science, but who are interested in acquiring competence in methods of data analysis. It requires completion of fifty-six units. Courses must be taken for a letter grade with a minimum passing grade of C–. Please be advised that DSC 40A/R serves as a prerequisite for required courses. Some upper-division courses also require the completion of DSC 40B/R as a prerequisite. DSC 40A/R-B/R can be taken for P/NP by data science minors.

Students majoring or minoring in computer science and engineering or business data science are not able to pursue a DSC minor. Additionally, students must have completed at least one quarter at UC San Diego to be eligible to add the minor. This policy is in place to ensure that students can become accustomed to their major course load before declaring the DSC minor.

Lower Division (thirty-six units)

  • COGS 9. Introduction to Data Science (4)
  • DSC 10/R. Principles of Data Science (4)
  • DSC 20/R. Programming and Basic Data Structures for Data Science (4)
  • DSC 30/R. Data Structures and Algorithms of Data Science (4)
  • DSC 80/R. The Practice and Application of Data Science (4)
  • MATH 18. Linear Algebra (4) or MATH 31AH. Honors Linear Algebra (4)
  • MATH 20A. Calculus for Science and Engineering (4)
  • MATH 20B. Calculus for Science and Engineering (4)
  • MATH 20C. Calculus and Analytical Geometry for Science and Engineering (4) or MATH 31BH. Honors Multivariable Calculus (4)

Upper Division (twenty units)

  • ECON 120A or MATH 183 or MATH 181A (4)
  • MATH 189. Exploratory Data Analysis and Inference (4)
  • DSC 140A or CSE 150A or CSE 151A or DSC 140B or DSC 148 or COGS 118A or COGS 118B
  • DSC 106. Introduction to Data Visualization (4) or COGS 108. Data Science in Practice (4)
  • Upper-division DSC course (DSC 100–DSC 196) (4)

Policies and Procedures for Data Science (DSC) Undergraduate Students

Data Science Undergraduate Admissions

Because of the large number of students interested in data science and the limited resources available to accommodate this demand, the university has declared the data science and business data science majors “selective.” This allows the Data Science Undergraduate Program to continue to offer the highest quality academic program to our students and avoid delays in time to degree due to lack of capacity in our courses.

All potential transfer students must indicate on the UC application if they wish to major in data science or business data science. Transfer students admitted to UC San Diego in fall 2025 or later will no longer be allowed to apply to selective majors in the summer application cycle after their first year.

Prospective Transfer Students

Required Transfer Major Preparation for Data Science

Prospective transfer students must complete the minimum major preparation course work to be considered for admission into either the data science or business data science major. Visit assist.org to find the complete listing of major preparation and transferable courses at your college. 

Please note that the courses listed in assist.org are for preparation for your major. The courses used in the screening requirements for admission into the major are those on our website.

Required:
  • MATH 18. Linear Algebra
  • MATH 20A. Calculus I for Science and Engineering
  • MATH 20B. Calculus II for Science and Engineering
  • MATH 20C. Calculus and Analytic Geometry for Science and Engineering
  • Minimum of one programming course in Java, C, C++, or Python. For colleges with ASSIST articulation agreements, we recommend that students take programming courses that articulate to DSC 20, DSC 30, CSE 8A-B, or CSE 11.

 For more information, please see: https://admissions.ucsd.edu/transfer/transfer-major-preparation.html.

Required Transfer Major Preparation for Business Data Science

Prospective transfer students must complete the minimum major preparation course work to be considered for admission into the major. Visit assist.org to find the complete listing of major preparation and transferable courses at your college.

Please note that the courses listed in assist.org are for preparation for your major. The courses used in the screening requirements for admission into the major are those on our website.

Required:
  • MATH 18. Linear Algebra
  • MATH 20A. Calculus I for Science and Engineering
  • MATH 20B. Calculus II for Science and Engineering
  • MATH 20C. Calculus and Analytic Geometry for Science and Engineering
  • MGT 45. Principles of Accounting or MGT 4. Financial Accounting

Continuing Students

UC San Diego students who would like to change from another major into the Data Science Undergraduate Program may apply to the major via the selective major application. Applications must be submitted on or before the deadline. See https://datascience.ucsd.edu/prospective-students/selective-major-application/ for details.

Eligibility requirements:

In addition to the eligibility criteria outlined on the selective major guidance page, data science and business data science require successful completion of the following three screening courses: MATH 18 or MATH 31AH, MATH 20C or MATH 31BH, and DSC 10.

Courses must be completed for a letter grade at the time of the selective major application to be eligible. Students may not have any outstanding grades for screening courses for any reason (e.g., incompletes, pending academic integrity case, etc.). Grades from transfer credit for screening courses will be used to determine eligibility.

For answers to commonly asked questions, please consult this FAQ page on the undergraduate education website.