Courses at UC Davis

This is a list of courses offered at UC Davis with content related to data science.

MATHEMATICS

  • MAT 128B: Numerical Analysis
  • MAT 160: Introduction to Analytics
  • MAT 167: Applied Linear Algebra
  • MAT 168: Optimization
  • MAT 189: Captstone Analytics Project
  • MAT 235B: Probability Theory
  • MAT 226B: Matrix Computations
  • MAT 271: Applied and Computational Harmonic Analysis
  • MAT 280: Past topics have included compressed sensing, harmonic analysis on graphs and networks
  • MAT 258A: Numerical Optimization
  • MAT 258B: Discrete and Mixed Integer Optimization
  • MAT 280: Topics in Convex Optimization

STATISTICS

  • STA 138: Categorical Data Analysis
  • STA 141: An Introduction to Statistical Computing (141A includes an introduction to R)
  • STA 206: Statistical Methods for Research I
  • STA 207: Statistical Methods for Research II
  • STA 208: Statistical and Machine Learning Topics
  • STA 224: Analysis of Longitudinal Data
  • STA 232: Applied Statistics I, II, III
  • STA 242: (Graduate Level) Introduction to Statistical Computing
  • STA 243: Computational Statistics

COMPUTER SCIENCE

  • List of 2017-2018 computer science course offerings
  • ECS 116: Databases for Non-Majors
  • ECS 132: Probabilistic and Statistical Modeling
  • ECS 145: Scripting Languages
  • ECS 158: Programming on Parallel Architectures
  • ECS 163: Information Interfaces
  • ECS 165: Database Systems
  • ECS 170: Artificial Intelligene
  • ECS 171: Machine Learning
  • ECS 175: Computer Graphics
  • ECS 188: Ethics and Information Age
  • ECS 230: Applied Numerical Linear Algebra
  • ECS 231: Large Scale Scientific Computing
  • ECS 256: Probabilistic Modeling
  • ECS 271: Machine Learning
  • EEC 274. Internet Measurements, Modeling and Analysis
  • ECS 275A: Advanced Computer Graphics
  • ECS 275B: Advanced Computer Graphics

OTHER

  • ANT291: Statistical Rethinking - A Bayesian Course with Examples in R and Stan, Richard McElreath. Currently not taught, but link contains reference material.
  • PHY 256: Physics of Information and Computation

Special Topics Courses

These are some "special topics" courses which are not taught regularly, the focal topic is subject to change, and/or may of particular interest.

Winter 2018

  • CEE/GEO 254: Introduction to R, Niemeier

Fall 2017

  • PLS 298: Applied statistical modeling for the environmetnal sciences, Latimer
  • EPI 202: Quantitative epidemiology, Harvey
  • PCS 205C: Structural equation modeling, Rhemtulla
  • ECS 265A: Distributed Database Systems, Sadoghi

Spring 2017

Winter 2017

  • ECL290: Data wrangling for ecologists, Peek & Lubell

Fall 2016

Spring 2016

Winter 2016

  • ECL 298:
  • ANT291: Statistical Rethinking - A Bayesian Course with Examples in R and Stan, McElreath
  • PHY 256: Physics of Information and Computation, Crutchfield
  • STA 250: Numerical Optimization, Hsieh

Fall 2015

  • BIM 289C: Special Topics in Computational Bioengineering: Genomic Big Data Analysis, Aviran

Winter 2015

  • ANT291: Statistical Rethinking - A Bayesian Course with Examples in R and Stan, McElreath
  • [MAT280]: Topics in Convex Optimization
  • PLS205: Design, analysis and interpretation of experiments, Dubcovsky