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Degrees and Courses at UC Davis

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Data Science-Related Degrees

Courses Involving Data Science

Interested in learning data science concepts, technologies, and methods? Check out the following courses, many of which are taught by DataLab faculty affiliates.

Are we missing a course? Please let us know!

Can’t take a full course? Check out our data science skills workshops.

Courses Taught by DataLab

Adventures in Data Science is a 2-quarter experiential education series comprised of the following two courses taught sequentially every winter through spring.

  • STS 115 Data Sense and Exploration: Critical Storytelling with Analysis
  • STS 195 Research in Data Studies

Courses by Department

Applied Biological Systems Technology

  • ABT 181N Concepts & Methods in Geographic Information Systems
  • ABT 182 Environmental Analysis using GIS

Agricultural & Resource Economics

  • ARE 106 Econometric Theory and Applications
  • ARE 256A&B Applied Econometrics I&II

Biology

  • BIS 015L Introduction to Data Science for Biologists
  • BIS 020Q Modeling in Biology
  • BIS/MAT 027A Linear Algebra with Applications to Biology

Biostatistics

  • BST 222 Survival Analysis
  • BST 223 Generalized Linear Models
  • BST 224 Analysis Of Longitudinal Data
  • BST 225 Clinical Trials
  • BST 227 Machine Learning in Genomics

Biotechnology

  • BIT 150 Applied Bioinformatics

Civil & Environmental Engineering

  • ECI 273 Water Resources Systems Engineering

Communications

  • CMN 102/102V Empirical Methods in Communication
  • CMN 110 Communication Networks
  • CMN 150V Computational Social Sciences
  • CMN 151 Simulating Communication Processes (with agent-based models)
  • CMN 152V Social Science with Online Data (web scraping, APIs, data analysis, Python)
  • CMN 170V Digital Technology & Social Change
  • CMN 210 Experimental Methods and Analysis in Communication
  • CMN 212 Web Science Research Methods
  • CMN 214 Analysis of Communication Networks
  • CMN 275Y Computational Social Science

Computer Science Engineering

  • ECS 11 Artificial Intelligence for All
  • ECS 17 Data, Logic and Computing
  • ECS 32A Introduction to Programming
  • ECS 32B Introduction to Data Structures
  • ECS 32C Implementation of Data Structures in C
  • ECS 36A Programming and Problem Solving
  • ECS 36B Software Development and object-oriented Programming
  • ECS 36C Data Structures, Algorithms and Programming
  • ECS 88 Ethics of Technology
  • ECS 111 Applied Machine Learning for Non-Majors
  • ECS 116 Databases for Non-Majors
  • ECS 117 Algorithms for Data Science
  • ECS 119 Data Processing Pipelines
  • ECS 122A/B Algorithm Design and Analysis
  • ECS 132 Probability and Statistical Modeling for Computer Science
  • ECS 140A/B Programming Languages
  • ECS 145 Scripting Languages and their Applications (R and Python as examples)
  • ECS 158 Programming on Parallel Architectures
  • ECS 161 Modern Programming Tools
  • ECS 163 Information Interfaces
  • ECS 165A/B Database Systems (SQL, XML, etc.)
  • ECS 170 Introduction to Artificial Intelligence
  • ECS 171 Machine Learning
  • ECS 173 Image Processing and Analysis
  • ECS 174 Computer Vision
  • ECS 175 Computer Graphics
  • ECS 177 Scientific Visualization
  • ECS 188 Ethics in an Age of Technology
  • ECS 193A/B Capstone Project
  • ECS 230 Applied Numerical Linear Algebra
  • ECS 231 Large-Scale Scientific Computing
  • ECS 256 Probability Models for Computer Science
  • ECS 271 Machine Learning and Discovery
  • EEC 274 Internet Measurements, Modeling and Analysis
  • ECS 275A&B Advanced Computer Graphics
  • ECS 289N Special Topics in Bioinformatics & Computational Biology
  • see more graduate courses on the ECS departmental website

Design

  • DES 111 Coding for Designers (formerly DES 037)

Ecology / Evolution & Ecology

  • ECL 224 Data Analysis and Visualization in R (D-DAVIS)
  • ECL 231 Mathematical Methods in Population Biology
  • ECL 233 Computational Methods in population biology
  • ECL 234 Bayesian Models – A Statistical Primer
  • ECL 290 Design and Analysis of Ecological Experiments
  • ECL 298 Group Study
  • EVE 225 Linear Mixed Modeling in Ecology and Evolution

Economics

  • ECN 140 Econometrics
  • ECN 240A&B Econometric Methods

Education

  • EDU 204A Quantitative Methods in Educational Research: Analysis of Correlational Designs
  • EDU 204B Quantitative Methods in Educational Research: Experimental Designs

Electrical & Computer Engineering

  • EEC 274 Internet Measurements, Modeling and Analysis

Epidemiology

  • EPI 202 Quantitative Epidemiology I: Probability
  • EPI 203 Quantitative Epidemiology II: Statistical Inference
  • EPI 204 Quantitative Epidemiology III: Statistical Models

Geography

  • GEO 200CN Quantitative Geography

Geology

  • GEL 160 Geological Data Analysis

Health Informatics

  • MHI 210 Longitudinal Data Analysis
  • MHI 289F Database and Knowledge Management
  • MHP 298H Modeling in Biology

Human Development

  • HDE 205 Longitudinal Data Analysis

Mathematics

  • MAT 128C Numerical Analysis in Different Equations
  • MAT 135A Probability
  • MAT 135B Stochastic Processes
  • MAT 167 Applied Linear Algebra
  • MAT 168 Optimization and Mathematical Programming
  • MAT 180 Mathematical Algorithms for Artificial Intelligence and Big Data Analysis
  • MAT 226C Numerical Methods: Ordinary Differential Equations
  • MAT 235A-C Probability Theory
  • MAT 236A Stochastic Dynamics and Applications
  • MAT 258A Numerical Optimization
  • MAT 271 Applied & Computational Harmonic Analysis
  • MAT 280 Topics in Pure and Applied Mathematics
    Past topics have included: compressed sensing; harmonic analysis on graphs and networks; Laplacian eigenfunctions – theory applications and comparisons; mathematical foundations of data science; mathematical foundations for big data.

Neurobiology, Physiology & Behavior

  • NPB 167 Computational Neuroscience
  • NPB 287A Topics in Theoretical Neuroscience
    Past topics have included machine learning, neural networks, statistical learning, bayesian models, information theory. Mixed grad/undergrad course.
  • PHY 256B Physics of Computation

Physics

  • PHY 256A Physics of Information
  • PHY 256B Physics of Computation

Plant Science

  • PLS 021 Application of Computers in Technology
  • PLS 120 Applied Statistics in Agricultural Sciences
  • PLS 123 Introduction to Plant and Crop Systems Modeling
  • PLS 124 Introduction to Digital Agriculture
  • PLS 125 Proximal and Remote Sensing of Plants
  • PLS 205 Experimental Design and Analysis
  • PLS 206 Applied Multivariate Modeling in Agricultural and Environmental Sciences
  • PLS 298 Applied Statistical Modeling for Environmental Science

Political Science

  • POL 211 Research Methods in Political Science
  • POL 212 Quantitative Analysis in Political Science
  • POL 213 Quantitative Analysis in Political Science II
  • POL 279 Political Networks: Methods and Applications

Psychology

  • PSC 12Y Data Visualization in the Social Sciences
  • PSC 103B Statistical Analysis of Psychological Data
  • PSC 107 Questionnaire & Survey Research Methods
  • PSC 120 Agent-Based Modeling
  • PSC 204A Statistical Analysis of Psychological Experiments
  • PSC 204B Causal Modeling of Correlational Data
  • PSC 205A Applied Multivariate Analysis of Psychological Data
  • PSC 205G Applied Longitudinal Data Analysis
  • PSC 290 Introduction to Scientific Programming for Psychology

Science and Technology Studies

  • STS 009 Beautiful Data
  • STS 101 Data and Society
  • STS 102 Artificial Intelligence in Society
  • STS 109 Visualization in Science: A Critical Introduction
  • STS 112 Visualizing Society with Data
  • STS 115 Data Sense and Exploration: Critical Storytelling with Analysis
  • STS 195 Research in Data Studies

Sociology

  • SOC 12Y Data Visualization in the Social Sciences
  • SOC 106 Intermediate Social Statistics
  • SOC 206 Quantitative Analysis in Sociology
  • SOC 298 Topics in Advanced Quantitative Methods in Social Science
  • SOC 298 Social Networks Analysis for Social Scientists

Statistics

  • STA 032 Gateway to Statistical Data Science
  • STA 035 Statistical Data Science I-III
  • STA 101 Applied Statistics for Biological Sciences
  • STA 103 Applied Statistics for Business and Economics
  • STA 104 Applied Statistical Methods: Nonparametric Statistics
  • STA 106 Applied Statistical Methods: Analysis of Variance
  • STA 108 Applied Statistical Methods: Regression Analysis
  • STA 130A&B Mathematical Statistics: Brief Course
  • STA 131A Introduction to Probability Theory
  • STA 135 Multivariate Data Analysis
  • STA 137 Applied Time Series Analysis
  • STA 138 Analysis of Categorical Data
  • STA 141A Fundamentals of Statistical Data Science (using R)
  • STA 141B Data & Web Technologies for Data Analysis (using Python)
  • STA 141C Big Data & High Performance Statistical Computing
  • STA 142A&B Statistical Learning I&II
  • STA 144 Sampling Theory of Surveys
  • STA 145 Bayesian Statistical Inference
  • STA 160 Practice in Statistical Data Science
  • STA 206 Statistical Methods for Research I
  • STA 207 Statistical Methods for Research II
  • STA 208 Statistical Methods in Machine Learning
  • STA 209 Optimization for Big Data Analytics
  • STA 220 Data and Web Technologies for Data Analysis
  • STA 224 Analysis of Longitudinal Data
  • STA 232A-C Applied Statistics I, II, III
  • STA 243 Computational Statistics
  • STA 260 Statistical Practice and Data Analysis

Wildlife, Fish & Conservation Biology

  • WFC 122 Population Dynamics and Estimation (modeling in R)
  • WFC 124 Sampling Animal Populations (statistical methods)
Research Toolkits Workshops Degrees & Courses at UC Davis