The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying,
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Training: Introduction to Clustering Using R
April 29, 2016
Students will be introduced to the basics of clustering using R.
Training: Computational Text Analysis in R
May 2, 2016 to May 6, 2016
This course introduces students to modern quantitative text analysis techniques, with the ultimate goal of providing the skills necessary to apply the methods in their own research.
Training: Geocoding and Mapping in R
May 4, 2016
This workshop will introduce geocoding - the process of determining the geographic coordinates for place names, zip codes or addresses.
April 27, 2016
Students will be introduced to the basics of machine learning using the caret R package.
April 20, 2016
Ensemble machine learning methods are often used when the true prediction function is not easily approximated by a single algorithm.
Training: Intro to Machine Learning in H2O
April 6, 2016
The focus of this workshop is machine learning using the H2O R and Python packages.
Training: Creating Maps in R
April 29, 2016
This workshop will introduce methods and libraries for mapping spatial data in R.
Training: Programming with Hierarchical Statistical Models: An Intro to the BUGS-compatible NIMBLE system
April 15, 2016
This tutorial will introduce attendees to the NIMBLE system for programming with hierarchical models in R.
Training: R for Data Science: Day 3
March 16, 2016
The R for Data Science workshop series is a four part course, designed to take novices in the R language for statistical computing and produce programmers who are competent in finding, displaying,
