Courses at UC Davis
This is a list of courses offered at UC Davis with content related to data science.
Upcoming Special Topics (Spring 2020)
- STS 112: Visualizing Society with Data – analysis and visualization of historical and contemporary data about populations and societies using R. (CRN 84358)
Departmental Courses
ANIMAL SCIENCES
- ABG 250 Mathematical Modeling in Biological Systems.
ANTHROPOLOGY
- ANT291: Statistical Rethinking – A Bayesian Course with Examples in R and Stan, Richard McElreath. Currently not taught, but link contains reference material. If you are interested in this content, check out DataLab’s research cluster on Applied Bayesian Statistics.
BIOSTATISTICS
- BST222. Survival Analysis
- BST223. Generalized Linear Models
- BST224. Analysis Of Longitudinal Data
- BST225. Clinical Trials
- BST226. Statistical Methods for Bioinformatics
- BST227. Machine Learning in Genomics.
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 Intelligence
- 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
ECOLOGY & EVOLUTION
- ECL298: Bayesian Models- A Statistical Primer
- ECL231: Mathematical Methods in Population Biology
- ECL290: Design and Analysis of Ecological Experiments
- ECL233: Computational methods in population biology
- ECL262: Advanced Population Dynamics
- ECL298: R Data Analysis and Visualization (D-DAVIS); Basics of Data Manipulation in R
- EVE231: Principles of Biological Data Analysis
ECONOMICS & AGRICULTURAL ECONOMICS
- ECN240A. Econometric Methods
- ECN240B. Econometric Methods
- ARE256. Applied Econometrics
EPIDEMIOLOGY
- EPI204A. Foundation of Statistical Methods
- EPI204B. Statistical Models, Methods, and Data Analysis for Scientists
GEOGRAPHY
- GEO200CN. Computational Methods in Geography Robert Hijmans
HYDROLOGY
- HYD273. Introduction to Geostatistics
MATHEMATICS
- MAT 128C: Numerical Analysis
- MAT 135A: Probability
- MAT 135B: Stochastic Processes
- MAT 160: Math for Data Analytics
- MAT 167: Applied Linear Algebra
- MAT 235C: Probability Theory
- MAT 226C: Numerical Methods
- MAT 280: Topics in Math. Past topics have included compressed sensing, harmonic analysis on graphs and networks.
- MAT 258A: Numerical Optimization
- MAT 280: Topics in Math
POLITICAL SCIENCE
- POL211. Research Methods in Political Science
- POL212. Quantitative Analysis in Political Science
- POL213. Quantitative Analysis in Political Science II
- POL279. Political Networks: Methods and Applications
PLANT SCIENCE
- PLS120. Applied Statistics in Agricultural Science
- PLS205. Experimental Design and Analysis
- PLS206. Applied Multivariate Modeling in Agricultural and Environmental Sciences
- PLS298. Applied Statistical Modeling for Environmental Science
PSYCHOLOGY
- PSC204A. Statistical Analysis of Psychological Experiments
PHYSICS
- PHY 256: Physics of Information and Computation.
STATISTICS
- STA 130A: Mathematical Statistics: Brief Course
- STA 130B: Mathematical Statistics: Brief Course
- STA 138: Analysis of Categorical Data
- STA 141A: Fundamentals of Statistical Data Science (using R)
- STA 141B: Data & Web Technologies for Data Analysis (previously has used Python)
- STA 141C: Big Data & High Performance Statistical Computing
- STA 144: Sample 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 224: Analysis of Longitudinal Data
- STA 232: Applied Statistics I, II, III
- STA 242: (Graduate Level) Introduction to Statistical Programming
- STA 243: Computational Statistics
SPECIAL TOPICS ARCHIVE
These are some “special topics” courses which are not taught regularly, the focal topic is subject to change, and/or may be of particular domain interest.
Spring 2018
- Graduate group in ecology “R-DAVIS” (Introduction to R for data analysis and visualization)
Winter 2018
- CEE/GEO 254: Introduction to R, Niemeier
Fall 2017
- PLS 298: Applied statistical modeling for the environmental sciences, Latimer
- EPI 202: Quantitative epidemiology, Harvey
- PCS 205C: Structural equation modeling, Rhemtulla
- ECS 265A: Distributed Database Systems, Sadoghi
Winter 2017
- ECL290: Data wrangling for ecologists, Peek & Lubell
- Fall 2016
- Evolutionary Algorithms, Herman
- Topology of Data, Tsuruga
- Modern tools for data collection, management and analysis, Caillaud
Spring 2016
- ECS 253/MAE 253: Network Theory, D’Souza
Winter 2016
- ECL 298:
- ANT 291: 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