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Data Science
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  1. Home
  2. Programs
  3. Undergraduate
  4. Data Science
  5. Minor

Minor

Minor
  • Data Science opens in a new tab
Program Minimum Units
22 Units
University Minimum Units
18 Units
Interests
Data and Information Sciences, Technology, Experimentation & Discovery, Public Health, Helping Others
Academic Areas
Mathematics & Data Sciences, Social Sciences

Overview

The undergraduate minor in Data Science is designed to complement major degree programs primarily in the humanities and social sciences. Students with an undergraduate Data Science minor gain practical knowledge of statistical data analysis methods related to their field of interest. The minor:

  • Equips students with exploratory and confirmatory data analysis tools, applied to diverse data types such as text, numbers, images, graphs, trees, and binary input.

  • Strengthens research in related fields by teaching students how to correctly apply these techniques to convey their conclusions.

(No previous programming or statistical background is assumed.)

Learning Outcomes

Students are expected to:

  1. Connect data to underlying phenomena and think critically about conclusions drawn from data analysis

  2. Be knowledgeable about programming abstractions so they can later design their own computational inferential procedures

Requirements

Program Requirements

Linear Algebra

Complete any of the following course(s):
ENGR 108

Introduction to Matrix Methods

3-5 Units
MATH 51

Linear Algebra, Multivariable Calculus, and Modern Applications

5 Units
MATH 104

Applied Matrix Theory

4 Units

Students who have taken CME 100 are recommended to take ENGR 108 to satisfy this requirement. 

Programming

Complete any of the following course(s):
CS 106A

Programming Methodology

3-5 Units
CS 106B

Programming Abstractions

3-5 Units

Probability

Complete any of the following course(s):
STATS 117

Introduction to Probability Theory

3-4 Units
or
CS 109

Introduction to Probability for Computer Scientists

3-5 Units
or
EE 178

Probabilistic Systems Analysis

3-4 Units
or
MS&E 120

Introduction to Probability

4 Units
STATS 118

Probability Theory for Statistical Inference

3-4 Units
or
MATH 151

Introduction to Probability Theory

4 Units
or
STATS 116X

Theory of Probability (accelerated)

5 Units

Students who take STATS 117, CS 109, EE 178 , or MS&E 120 for their major or another minor are required to take STATS 118 or MATH 151 to satisfy this requirement.

STATS 116X is only recommended for advanced undergraduate students with strong mathematical preparation, no prior background in probability, and preference for an accelerated pace.

Statistics

Complete any of the following course(s):
ECON 102A

Introduction to Statistical Methods (Postcalculus) for Social Scientists

5 Units
HUMBIO 88

Introduction to Statistics for the Health Sciences

4 Units
HUMBIO 89

Introduction to Health Sciences Statistics

3 Units
MS&E 125

Introduction to Applied Statistics

4 Units
STATS 110

Introduction to Statistics for Engineering and the Sciences

5 Units
STATS 141

Introduction to Statistics for Biology

5 Units
STATS 191

Introduction to Applied Statistics

3 Units
STATS 200

Introduction to Theoretical Statistics

3-4 Units
STATS 200Q

Philosophical Foundations of Statistics

4 Units
STATS 203

Regression Models and Analysis of Variance

3 Units

Data Mining and Machine Learning

Complete any of the following course(s):
DATASCI 112

Principles of Data Science

5 Units
POLISCI 150B

Machine Learning for Social Scientists

3-5 Units
STATS 202

Statistical Learning and Data Science

3 Units
STATS 202F

Statistical Learning and Data Science [Flipped]

3 Units
STATS 202V

Statistical Learning and Data Science [Virtual]

3 Units

Data Science Methodology

Students must complete one course fulfilling Data Science methodology from a cognate field of interest. Suggested courses are included here. The Data Science Program must approve other courses via requirement inquiry form opens in a new tab.

Complete any of the following course(s):
BIOMEDIN 202

An overview of Biomedical Data Science

3 Units
COMM 177I

Investigative Watchdog Reporting

4-5 Units
CS 224N

Natural Language Processing with Deep Learning

3-4 Units
CS 224W

Machine Learning with Graphs

3-4 Units
CS 246

Mining Massive Data Sets

3-4 Units
CS 279

Computational Biology: Structure and Organization of Biomolecules and Cells

3 Units
DATASCI 154

Data Science for Social Impact

5 Units
DATASCI 156

Thinking and Making with Data

5 Units
EARTHSYS 141

Remote Sensing of the Oceans

3-4 Units
EARTHSYS 240

Data Science for Geoscience

3 Units
ECON 102B

Applied Econometrics

5 Units
ECON 102C

Advanced Topics in Econometrics

5 Units
ECON 137

Decision Modeling and Information

5 Units
ECON 151

Tackling Big Questions Using Social Data Science

5 Units
ECON 291

Social and Economic Networks

4 Units
ENGLISH 184E

Literary Text Mining

5 Units
ESS 171

Climate Models and Data

3 Units
ESS 367

AI for Biodiversity Science and Conservation

3 Units
GEOPHYS 115

Taking the Pulse of the Planet

3 Units
HUMBIO 151R

Biology, Health and Big Data

3 Units
MS&E 125

Introduction to Applied Statistics

4 Units
MS&E 135

Networks

3 Units
MS&E 226

Fundamentals of Data Science: Prediction, Inference, Causality

3 Units
MS&E 245A

Investment Science

4 Units
POLISCI 150B

Machine Learning for Social Scientists

3-5 Units
POLISCI 150C

Causal Inference for Social Science

3-5 Units
PUBLPOL 185

Data Science for Environmental Business

5 Units
SOC 10

Introduction to Computational Social Science

4 Units
SOC 126

Introduction to Social Networks

4 Units
SOC 180A

Foundations of Social Research

4 Units
SOC 180B

Introduction to Data Analysis

4 Units
SUSTAIN 101C

Climate 101

3 Units
SYMSYS 1

Minds and Machines

4 Units

For any questions about program requirements, please reach out to the Student Services Specialist via datasciencemajor-inquiries@lists.stanford.edu.