Courses

Title: Data Science Related Courses
Author: DSI
Tags: Courses

# Courses at UC Davis

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

### ANIMAL SCIENCES

* [ABG 250](http://egsa.ucdavis.edu/wp-content/uploads/ABG_250_Modeling-Course-Information.pdf) Mathematical Modeling in Biological Systems.

### ANTHROPOLOGY

* [ANT291](http://xcelab.net/rm/?page_id=596): Statistical Rethinking – A Bayesian Course with Examples in R and Stan, [Richard McElreath](http://xcelab.net/rm/). Currently not taught, but link contains reference material.

### BIOSTATISTICS

* BST222. Survival Analysis
* BST223. Generalized Linear Models
* BST224. Analysis Of Longitudinal Data
* BST225. Clinical Trials
* BST226. Statistical Methods for Bioinformatics

### [COMPUTER SCIENCE](http://www.cs.ucdavis.edu/courses/descriptions/)

* [List of 2017-2018 computer science course offerings](http://www.cs.ucdavis.edu/wp-content/uploads/2014/09/2017-2018-Tentative-Schedule-7.pdf)
* [ECS 116](http://www.cs.ucdavis.edu/blog/ecs-116-databases-non-majors/): 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](http://www.cs.ucdavis.edu/blog/ecs-188-ethics-age-technology/): Ethics and Information Age
* ECS 230: Applied Numerical Linear Algebra
* [ECS 231](http://www.cs.ucdavis.edu/blog/ecs-231-large-scale-scientific-computation/): Large Scale Scientific Computing
* [ECS 256](http://heather.cs.ucdavis.edu/~matloff/256/AnnounceW16.html): Probabilistic Modeling
* [ECS 271](http://www.cs.ucdavis.edu/blog/ecs-271-machine-learning-discovery/): Machine Learning
* [EEC 274](http://www.ece.ucdavis.edu/blog/eec274/). Internet Measurements, Modeling and Analysis
* [ECS 275A](http://www.cs.ucdavis.edu/blog/ecs-275a-advanced-computer-graphics/): Advanced Computer Graphics
* [ECS 275B](http://www.cs.ucdavis.edu/blog/ecs-275b-advanced-computer-graphics/): Advanced Computer Graphics

### ECOLOGY & EVOLUTION

* 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](http://desp.ucdavis.edu/people/robert-j-hijmans)

### HYDROLOGY

* HYD273. Introduction to Geostatistics

### [MATHEMATICS](http://catalog.ucdavis.edu/programs/MAT/MATcourses.html#pgfId-3873523)

* MAT 128C: [Numerical Analysis](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=78)
* MAT 135A: [Probability](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=80)
* MAT 135B: [Stochastic Processes](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=81)
* MAT 160: [Math for Data Analytics](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=157)
* MAT 167: [Applied Linear Algebra](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=114)
* MAT 235C: [Probability Theory](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=50)
* MAT 226C: [Numerical Methods](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=144)
* MAT 280: Topics in Math. Past topics have included compressed sensing, harmonic analysis on graphs and networks.
* MAT 258A: [Numerical Optimization](https://www.math.ucdavis.edu/courses/syllabus_detail?cm_id=28)
* MAT 280: [Topics in Math](https://www.math.ucdavis.edu/courses/course_detail?term=201803&select_reg_id=12369)

### 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](http://csc.ucdavis.edu/~chaos/courses/ncaso/): Physics of Information and Computation.

### [STATISTICS](http://www-stat.ucdavis.edu/courses/index.html)

* 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 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.

* 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](https://faculty.engineering.ucdavis.edu/sadoghi/teaching/): Distributed Database Systems, Sadoghi
* Winter 2017
* [ECL290](http://environmentalpolicy.ucdavis.edu/files/cepb/Social%20Ecological%20Systems%20Syllabus%20Winter%202014_0.pdf): Data wrangling for ecologists, Peek & Lubell
* Fall 2016
* [Evolutionary Algorithms](Courses/Fall2016/eci289I-announcement.pdf), Herman
* [Topology of Data](Courses/Fall2016/DataTopology.txt), Tsuruga
* [Modern tools for data collection, management and analysis](Courses/Fall2016/dataCollectionAndManagement.pdf), Caillaud
* Spring 2016
* [ECS 253/MAE 253](http://mae.engr.ucdavis.edu/dsouza/ecs253): Network Theory, D’Souza
* Winter 2016
* ECL 298:
* [ANT291](http://xcelab.net/rm/?page_id=596): Statistical Rethinking – A Bayesian Course with Examples in R and Stan, [McElreath](http://xcelab.net/rm/)
* [PHY 256](http://csc.ucdavis.edu/~chaos/courses/ncaso/): Physics of Information and Computation, Crutchfield
* [STA 250](http://www.stat.ucdavis.edu/~chohsieh/teaching/STA250_Winter2016/main.html): Numerical Optimization, Hsieh
* Fall 2015
* BIM 289C: Special Topics in Computational Bioengineering: Genomic Big Data Analysis, [Aviran](http://bme.ucdavis.edu/aviranlab/)
* Winter 2015
* [ANT291](http://xcelab.net/rm/?page_id=596): Statistical Rethinking – A Bayesian Course with Examples in R and Stan, [McElreath](http://xcelab.net/rm/)
* [MAT280]: Topics in Convex Optimization
* [PLS205](http://www.plantsciences.ucdavis.edu/agr205/): Design, analysis and interpretation of experiments, Dubcovsky