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LinkedIn Learning

Master R for Data Science

via LinkedIn Learning Path

Overview

Learn the most popular data-science-specific language: R! This learning path provides a strong foundation of skills and knowledge on which to build your coding resume.
  • Learn how R works, from the foundational concepts on up.
  • Practice using R with two of the most common tools in data science: Excel and Tableau.
  • Explore the applied use of R in social network analysis.

Syllabus

Courses under this program:
Course 1: Learning R
-Learn the basics of R, the free, open-source language for data science. Discover how to use R and RStudio for beginner-level data modeling, visualization, and statistical analysis.

Course 2: Code Clinic: R
-Practice coding with R. Explore common R programming challenges, and then compare the results with other programming languages in the Code Clinic series.

Course 3: Data Wrangling in R
-Learn about the principles of tidy data and discover how to import, transform, clean, and wrangle data using the R programming language.

Course 4: R Essential Training: Wrangling and Visualizing Data
-Learn how to wrangle data and create meaningful visualizations with R, the programming language powering modern data science.

Course 5: Social Network Analysis Using R
-Examine the relationships and trends among social networks in new and exciting ways. Learn how to perform social network analysis with R.

Course 6: R Programming in Data Science: Setup and Start
-Learn how to choose and install a version of R-base R, tidyverse R, R Open, or Bioconductor R-and install useful R packages.

Course 7: Integrating Tableau and R for Data Science
-Discover how to combine Tableau and R to provide your business with the ability to see and understand your data. Learn how to integrate these platforms and when to use either one.

Course 8: R for Excel Users
-Update your data science skills by learning R. Learn how data analysis and statistics operations are run in Excel versus R and how to move data back and forth between each program.

Course 9: Machine Learning with Logistic Regression in Excel, R, and Power BI
-Learn how to perform logistic regression using R and Excel and use Power BI to integrate these methods into a scalable, sharable model.

Courses

Taught by

Barton Poulson, Mark Niemann-Ross, Mike Chapple, Curtis Frye, Ben Sullins, Conrad Carlberg and Helen Wall

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