Nebraska.Code() Sessions tagged data science

Introduction to the R Language and Ecosystem

This session will introduce you to R, a general purpose programming language and software environment that is popular for data analysis and visualization. We will introduce the R language, focusing on examples of the kinds of things that R excels at like data wrangling, exploratory data analysis, statistical computing, machine learning, and data visualization.

We'll also introduce the R ecosystem, including the tidyverse, an opinionated collection of R packages designed to make data science fast, fluent, and fun. We'll see examples of how you can create documents containing code and graphics using tools like R Markdown, as well as creating and publishing interactive data-driven web applications using Shiny.

No prior knowledge of R is required. The emphasis will be on breadth rather than depth. You'll come away with a basic understanding of what R is all about and suggestions for how to learn more.

Speaker

David Body

David Body

President, Big Creek Software, LLC

R Programming: Getting Started in Data Science

R programming has become a useful language in the field of data science. It has allowed practitioners to apply statistical a wide number of data sources. But where does one start to learn the principles in the language, and also develop models that are useful?

This workshop will go through the basic usage of R programming including: * Installing R programming * The basic programming protocols in R, including the value of libraries * The basics of RStudio (the IDE used for R), * R Markdown * How data is accesssed (API, libraries, data files) * Data sources and ideas for researching data * Overview of basic models (focus on regression) * Data Science examples will be noted * Data visualization with ggplot and other data visualization options

Speaker

Pierre DeBois

Pierre DeBois

Founder, Zimana