Introduction to Data Science with R

Introduction to Data Science with R

Video Training

The R programming language has arguably become the single most important tool for computational statistics, visualization, and data science. This Learning Path will take you step-by-step through the R basics you’ll need to succeed as a data scientist.

Below are the video training courses included in this Learning Path.

1

Learning To Program With R

Presented by Stuart Greenlee 4 hours 18 minutes

This video covers all the basics you need from installing R studio to saving different types of data. You’ll learn how to use statistical functions, matrix operations, and string functions and how to plot, using scatter plots, probability plots, and plotting arguments. You’ll extract model information, and learn about conditional statements and user-defined functions, including how to write and de-bug functions. Working files are included, allowing you to follow along with the video.

2

Introduction to Data Science with R

Presented by Garrett Grolemund 8 hours 36 minutes

This video covers the three skill sets of data science: computer programming (with R), manipulating data sets (including loading, cleaning, and visualizing data), and modeling data with statistical methods. You’ll learn R’s syntax and grammar as well as how to load, save, and transform data, generate beautiful graphs, and fit statistical models to the data.

3

Writing Great R Code

Presented by Richard Cotton 59 minutes

The jump from “writing code like a statistician” to “being a statistical programmer” in R isn’t that far. This webcast covers a few simple skills that will get you started, including: writing stylish code; finding bad functions with the sig package; writing robust code with the assertive package; testing your code with the testthat package; and documenting your code with the roxygen2 package.

4

Data Visualization in R with ggplot2

Presented by Kara Woo 1 hour 1 minute

You’ll learn how to create great looking, insightful data visualizations using the R package ggplot2. This video covers the principles of data visualization and the specifics of how to use ggplot2 to create and customize a variety of visualizations. You’ll come away with a thorough understanding of ggplot2, allowing you to work with the advanced tools required on complex projects and interactive visualizations.

5

Reproducible Research and Reports with R Markdown

Presented by Garrett Grolemund 2 hours 9 minutes

R Markdown allows you to make a completely reproducible, parameter-set, and automatable R report—and export that report into a multitude of formats (HTML, Word, .js slide show, interactive web app, etc). And it does it really fast. This video shows you everything you need to add this package to your bag of tricks.

6

Introduction to Shiny

Presented by Garrett Grolemund 3 hours 13 minutes

Shiny combines the computational power of R and the interactivity of the web to produce highly interactive reports and visualizations. This video will show you how to use it to build an app. You’ll learn about reactive programming and why it differs from functional programming and how to use the Shiny UI and the toolsets it offers to customize the appearance of your Shiny app.