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Data Science Minor Requirements 2024-2025
These degree requirements apply to students who declared between September 1, 2024 and August 31, 2025.
Course Requirements
Linear Algebra (5 units)
Select one course:
- ENGR 108: Introduction to Matrix Methods
- Math 51: Linear Algebra, Multivariable Calculus, and Modern Applications
- Math 104: Applied Matrix Theory
*Students who've taken CME 100 are recommended to take ENGR 108 to satisfy this requirement.
Programming (5 units)
Select one course:
- CS 106A: Programming Methodology (CS 106AP and CS 106AJ also satisfy this requirement)
- CS 106B: Programming Abstractions
Probability (3-5units)
Select one course:
- CS 109: Introduction to Probability for Computer Scientists
- EE 178: Probabilistic Systems Analysis
- MATH 151: Introduction to Probability Theory
- MS&E 120: Introduction to Probability
- STATS 117: Introduction to Probability Theory
- STATS 118: Probability Theory for Statistical Inference
*Students who've taken CS 109 / EE 178 / MS&E 120 for their degree will be required to take STATS 118 or MATH 151 to satisfy this requirement.
Statistics (3-5 units)
Select one course:
- ECON 102A: Introduction to Statistical Methods (Postcalculus) for Social Scientists
- HUMBIO 88: Introduction to Statistics for the Health Sciences
- HUMBIO 89: Introduction to Health Sciences Statistics
- MS&E 125: Introduction to Applied Statistics
- STATS 110: Introduction to Statistics for Engineering and the Sciences
- STATS 141: Introduction to Statistics for Biology
- STATS 191: Introduction to Applied Statistics
- STATS 200: Introduction to Theoretical Statistics
Data Mining and Machine Learning (3-5 units)
Select one course:
- DATASCI 112: Principles of Data Science
- POLISCI 150B: Machine Learning for Social Scientists
- STATS 202: Statistical Learning and Data Science
Data Science Methodology from the cognate field of interest (2-5 units)
Note that courses may not be offered every year: refer to ExploreCourses.
Select one course:
- BIODS 210 - Configuration of the US Healthcare System and the Application of Big Data/Analytics
- BIOMEDIN 202 - BIOMEDICAL DATA SCIENCE
- COMM 177I - Investigative Watchdog Reporting
- CS 224N: Natural Language Processing with Deep Learning
- CS 224W - Machine Learning with Graphs
- CS 279 - Computational Biology: Structure and Organization of Biomolecules and Cells
- DATASCI 154: Solving Social Problems with Data
- EARTHSYS 240: Data Science for Geoscience
- ECON 102B - Applied Econometrics
- ECON 102C - Advanced Topics in Econometrics
- ECON 137 - Decision Modeling and Information
- ECON 151 - Tackling Big Questions Using Social Data Science
- ECON 291 - Social and Economic Networks
- ENGLISH 184E - Literary Text Mining
- ESS 171 - Climate Models and Data
- GEOPHYS 115: Taking the Pulse of the Planet
- IMMUNOL 206 - Introduction to Applied Computational Tools in Immunology
- MS&E 125 - Introduction to Applied Statistics
- MS&E 135 - Networks
- MS&E 226: Fundamentals of Data Science: Prediction, Inference, Causality
- MS&E 245A - Investment Science
- POLISCI 150B - Machine Learning for Social Scientists
- POLISCI 150C: Causal Inference for Social Science
- PUBLPOL 185: Data Science for Environmental Business
- SOC 10 - Introduction to Computational Social Science
- SOC 126 - Introduction to Social Networks
- SOC 180A - Foundations of Social Research
- SOC 180B - Introduction to Data Analysis
- SYMSYS 1 - Minds and Machines
Additional Information
- All courses for the minor must be taken for a letter grade.
- Data Science will accept a letter grade or credit for all major/minor courses from the 2020-21 academic year.
- Data Science will also accept courses that are only offered as S/NC (i.e. letter grade option not available).
- A note about double counting:
- Students may not overlap ("double-count") courses when completing multiple major and/or minor requirements, unless overlapping courses constitute introductory skill requirements (for example, introductory math or a foreign language).
- For majors & minors with overlapping requirements, the courses that may be double counted are Math 51, ENGR 108, CS 106A/B. Beyond these, students would need to find another suitable course to satisfy the requirements for the minor.
- Any changes to the initial course of study should be approved in advance by the department.
- If you have any questions or would like to talk more about the minor, please reach out to the Student Services Specialist.
Typical Paths to the Minor
Frosh: Math 21, Programming
Frosh: Math 21, Programming
Sophomore: Linear Algebra, Probability
Sophomore: Linear Algebra, Probability
Junior: Statistics, Data Science Methodology
Junior: Statistics, Data Science Methodology
Senior: Data Mining and Machine Learning
Senior: Data Mining and Machine Learning
Frosh: (AP Calculus), Programming
Frosh: (AP Calculus), Programming
Sophomore: Linear Algebra, Probability
Sophomore: Linear Algebra, Probability
Junior: Statistics, Data Science Methodology
Junior: Statistics, Data Science Methodology
Senior: Data Mining and Machine Learning
Senior: Data Mining and Machine Learning