LinkedIn Learning
Free Trial Available
English
Certificate Available
15 hours worth of material
selfpaced
Overview
The R language is one of the top two languages you need to learn if you want build the strongest career path possible in data science. (The other is Python.) After mastering the basics of R, take your skills in data science into highly valued areas of specialty with this learning path.
- Learn R in the context of the R tidyverse.
- Createdata visualizations and presentations.
- Developbusiness analytics skills at an advanced level in Excel.
Syllabus
- Course 1: R Data Science Code Challenges
- Test your knowledge of R programming in this Code Challenges course.
- Course 2: Learning the R Tidyverse
- Learn to integrate the tidyverse into your R workflow and get new tools for importing, filtering, visualizing, and modeling research and statistical data.
- Course 3: Business Analytics: Data Reduction Techniques Using Excel and R
- Learn how to carry out cluster analysis and principal components analysis using R, the open-source statistical computing software.
- Course 4: Creating Interactive Presentations with Shiny and R
- Make the results of big data analysis more compelling and clear. Learn how to create interactive presentations and dashboards with RStudio and Shiny.
- Course 5: R: Interactive Visualizations with htmlwidgets
- Learn how to rapidly create rich, interactive data visualizations with R and htmlwidgets—packages that connect R to popular JavaScript libraries like Plotly, Leaflet, and DT.
- Course 6: Data Visualization in R with ggplot2
- Discover how to create informative and visually appealing data visualizations using ggplot2, the leading visualization package for R.
Taught by
Mark Niemann-Ross, Charlie Joey Hadley, Conrad Carlberg, Charlie Joey Hadley, Charlie Joey Hadley and Mike Chapple
