# B.S. Degree Requirements 2023-2024

These updated degree requirements apply to students who declare on or after September 1, 2023.

Following careful review by the Data Science team, there are two changes from the previous year's requirements:

- DATASCI 112 has been added as a gateway course.
- Two official subplans have been created, and students will be required to choose one:
- Mathematics and Computation subplan
- This option will allow students to follow the same requirements as those in the previous academic year (with the addition of DATASCI 112 as a gateway course). Some requirements have simply been rearranged to fit into the structure of the subplan.
- This subplan is largely in response to feedback from students that the words Mathematics and Computation are important in reflecting the content of the major. Thus, the subplan will allow this language to be included in the name of the degree.

- Biology and Medicine subplan
- This option is intended for students with a particular interest in biological processes and the analysis of health and biological data. This subplan includes a set of biology classes that is recommended for students interested in applying to medical school.

- Mathematics and Computation subplan

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B.S. Core Courses

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Gateway Course (4 units)

- Principles of Data Science (DATASCI 112, 4 units)

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Math Core (19 units)

- One of the following sequences:
- Multivariable Calculus and Linear Algebra

Linear Algebra, Multivariable Calculus, and Modern Applications (Math 51, 5 units)

Integral Calculus of Several Variables (Math 52, 5 units)

Ordinary Differential Equations with Linear Algebra (Math 53, 5 units) - Modern Mathematics: Continuous Methods (a proof-oriented sequence)

MATH 61CM (5 units)

MATH 62CM (5 units)

MATH 63CM (5 units) - Modern Mathematics: Discrete Methods (a proof-oriented sequence)

MATH 61DM (5 units)

MATH 62DM (5 units)

MATH 63DM (5 units)

- Multivariable Calculus and Linear Algebra
- One of the following:
- Applied Matrix Theory (Math 104, 4 units)
- Linear Algebra and Matrix Theory (Math 113, 4 units)

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Computation Core (15 units)

- Mathematical Foundations of Computing (CS 103, 5 units)
- Programming Methodology (CS 106A, 5 units)
- Programming Abstractions (CS 106B or X, 5 units)

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Optimization Core (6-11 units)

Option A: Optimization Core Set of Two

- One of the following:
- Introduction to Optimization (Accelerated) (MS&E 211X, 3-4 units)
- Convex Optimization I (EE 364A, 3 units)

- One of the following:
- Stochastic Modeling (MS&E 221, 3 units)
- Introduction to Stochastic Processes I (STATS 217, 3 units)

Option B: Optimization Core Set of Three

- Choose three of the following:
- Introduction to Optimization (MS&E 111 or 111X, 3-4 units)
- Introduction to Stochastic Modeling (MS&E 121, 4 units)
- Introduction to Optimization Theory (MS&E 213, 3 units)
- Stochastic Modeling (MS&E 221, 3 units)
- Introduction to Stochastic Control with Applications (MS&E 251, 3 units)

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Statistics Core (11-13 units)

- One of the following:
- Theory of Probability (STATS 116, 5 units)
- Theory of Probability I (STATS 117, 3 units) AND Theory of Probability II (STATS 118, 3 units)
- Introduction to Probability Theory (Math 151, 4 units)

- Introduction to Statistical Inference (STATS 200, 4 units)
- One of the following
- Introduction to Applied Statistics (STATS 191, 3 units)
- Introduction to Regression Models and Analysis of Variance (STATS 203, 3 units)

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Ethics Core (3-5 units)

- One of the following:
- Justice (POLISCI 103, 5 units)
- Ethics, Public Policy, and Technological Change (CS 182, 5 units)*
- Data Privacy and Ethics (MS&E 234, 3 units)
- Introduction to Moral Philosophy (ETHICSOC 20, 4-5 units)
- The Politics of Algorithms (Comm 154 / COMM 254 / CSRE 154T / SOC 154, 5 units)

*CS 182W cannot be double-counted for the ethics requirement and the WIM requirement.

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Subplan (Required - Choose one)

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Mathematics and Computation Subplan (19-22 units)

- Two of the following:
- Introduction to Scientific Computing (CME 108, 3 units)
- Computer Organization and Systems (CS 107, 5 units)
- Introduction to the Theory of Computation (CS 154, 4 units)
- Design and Analysis of Algorithms (CS 161, 5 units)

- One of the following:
- Data Mining and Analysis (STATS 202, 3 units)
- Introduction to Statistical Learning (STATS 216, 3 units)
- Modern Applied Statistics: Learning (STATS 315A, 3 units)
- Topics in Causal Inference (STATS 209A/MS&E 327, 3 units)
- Design of Experiments (STATS 263, 3 units)

- Three Data Science electives (at least 9 units)

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Biology and Medicine Subplan (18-21 units)

- One
- Introduction to Scientific Computing (CME 108, 3 units)
- Mathematical Modeling of Biological Systems (CME 209, 3 units)
- Computer Organization and Systems (CS 107, 5 units)
- Introduction to the Theory of Computation (CS 154, 4 units)
- Design and Analysis of Algorithms (CS 161, 5 units)
- Foundations of Computational Human Genomics (CS 173A, 3-4 units)
- Modeling Biomedical Systems (CS 270, 3 units)
- Representations and Algorithms for Computational Molecular Biology (CS 274, 3-4 units)
- Computational Biology: Structure and Organization of Biomolecules and Cells (CS 279, 3 units)

- One of the following sets:
- Option A
- Genetics (BIO 82, 4 units)
- Biochemistry & Molecular Biology (BIO 83, 4 units)
- Physiology (BIO 84, 4 units)
- Cell Biology (BIO 86, 4 units)

- Option B
- Genetics, Evolution, and Ecology (HUMBIO 2A, 5 units)
- Cell and Developmental Biology (HUMBIO 3A, 5 units)
- The Human Organism (HUMBIO 4A, 5 units)

- Option A

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Additional Degree Requirements

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Writing in the Major (WIM) (3-5 units)

- One of the following:
- Data Narratives (MCS 120 / DataSci 120)
- Ethics, Public Policy, and Technological Change (CS 182W, 5 units)*
- Applied Group Theory (MATH 109, 4 units)
- Applied Number Theory and Field Theory (MATH 110, 4 units)
- Groups and Rings (MATH 120, 4 units)
- Fundamental Concepts of Analysis (MATH 171, 4 units)
- Modern Statistics for Modern Biology (STATS 155, 3 units)

*CS 182W cannot be double-counted for the ethics requirement and the WIM requirement.

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Capstone Experience (1 unit or more)

Data Science B.S. majors will have the opportunity to integrate the knowledge and skills acquired during their studies and think independently and creatively using the tools of the discipline during a capstone experience, which is an essential part of the undergraduate program. There are a variety of ways to complete the Capstone requirement, both within and outside Data Science.

To satisfy the capstone requirement, choose one of the following options:

- The Data Science Experience (DATASCI 190, 1 unit). This course satisfies the Capstone Requirement if taken after or concurrently with Data Narratives (DATASCI 120, 3 units). DATASCI 120 can be double-counted for the WIM and part of this capstone option.
- Data Science Practicum I (DATASCI 192A, 2 units) & Data Science Practicum II (DATASCI 192B, 2 units)
- Data Science Honors Program
- Notation in Science Communication
- Completing a project-based class in another department that involves significant data science work could also be considered for the capstone requirement. The class would need to be pre-approved by the program. Examples from the past include BIODS 217 and HISTORY 238C.
- Completing an independent research project in Data Science with a final portfolio could also be considered for the capstone requirement. This project would need to be pre-approved by the program.