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Data Science Minor Requirements 2023-2024

These degree requirements apply to students who declared between September 1, 2023 and August 31, 2024.

 

Data Science Minor Form

Course Requirements

Linear Algebra (5 units)

Select one course:

  • CME 100: Vector Calculus for Engineers
  • Math 51: Linear Algebra, Multivariable Calculus, and Modern Applications
Programming (5 units)
  • CS 106A: Programming Methodology (CS 106AP and CS 106AJ also satisfy this requirement)
Programming in R (1-4 units)

Select one course:

  • STATS 32: Introduction to R for Undergraduates 
  • STATS 48N: Riding the Data Wave 
  • STATS 195: Introduction to R 
  • THINK 3: Breaking Codes, Finding Patterns 
Data Science (3-5 units)

Select one course:

  • DATASCI 112: Principles of Data Science (STATS 112)
  • DATASCI 154: Solving Social Problems with Data
  • CS 102: Working with Data - Tools and Techniques
  • MS&E 226: Fundamentals of Data Science: Prediction, Inference, Causality
  • STATS 60: Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160)
  • STATS 101: Data Science 101
  • STATS 191: Introduction to Applied Statistics (Note: STATS 191 cannot count for both the Statistics and Data Science requirements)
Statistics (3-5 units)

Select one course:

  • ECON 102A: Introduction to Statistical Methods (Postcalculus) for Social Scientists
  • STATS 141: Biostatistics
  • STATS 191: Introduction to Applied Statistics (Note: STATS 191 cannot count for both the Statistics and Data Science requirements)
  • STATS 211: Meta-research: Appraising Research Findings, Bias, and Meta-analysis
Data Mining and Analysis (3 units)

Select one course:

  • STATS 202: Data Mining and Analysis
  • STATS 216: Introduction to Statistical Learning
Data Science Methodology from the cognate field of interest (2-5 units)

Note that courses may not be offered every year: refer to ExploreCoursesSelect at least one course.

Suggested courses include:

  • BIODS210 - Configuration of the US Healthcare System and the Application of Big Data/Analytics
  • BIOMEDIN202 - BIOMEDICAL DATA SCIENCE
  • COMM177I - Investigative Watchdog Reporting
  • CS224W - Machine Learning with Graphs
  • CS279 - Computational Biology: Structure and Organization of Biomolecules and Cells
  • ECON102B - Applied Econometrics
  • ECON102C - Advanced Topics in Econometrics
  • ECON137 - Decision Modeling and Information
  • ECON151 - Tackling Big Questions Using Social Data Science
  • ECON291 - Social and Economic Networks
  • ENGLISH184E - Literary Text Mining
  • ESS171 - Climate Models and Data
  • IMMUNOL206 - Introduction to Applied Computational Tools in Immunology
  • MS&E125 - Introduction to Applied Statistics
  • MS&E135 - Networks
  • MS&E245A - Investment Science
  • POLISCI150B - Machine Learning for Social Scientists
  • SOC10 - Introduction to Computational Social Science
  • SOC126 - Introduction to Social Networks
  • SOC180A - Foundations of Social Research
  • SOC180B - Introduction to Data Analysis
  • SYMSYS1 - Minds and Machines

Additional Information

  • All courses for the minor must be taken for a letter grade, with the exception of the Data Mining requirement.
    • 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). 
  • An overall 2.75 grade point average (GPA) is required for courses fulfilling the minor.
  • 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, CME 100, CS 106A/B, & STATS 60. 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: Programming in R, Math 21, CS 106A
Sophomore: Linear Algebra, Data Science course
Junior: Statistics course, Data Science Methodology course
Senior: Data Mining and Analysis
Frosh: (AP Calculus), Programming in R, CS 106A
Sophomore: Linear Algebra, Data Science course
Junior: Statistics course, Data Science Methodology course
Senior: Data Mining and Analysis