R for Business Analytics & Data Science

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Whether you're just getting started to a journey in learning R or you would like to become proficient with the more advanced topics, take your R skills to the next level with these classes.

Beginner R1

This course will expose students to the underlying concepts of “R”. Key topics include the RStudio IDE, R fundamentals, installing and using packages, working with vectors and data frames, and running basic models. After completing this module, participants will learn to work with R environment, conduct basic of programming in R, and use the Tidyverse for data manipulation.

 half-day in-classroom and additional online resources       Hybrid          $135


Key Topics
  • RStudio IDE
  • Working with packages
  • Conditional statements
  • Vectors and data frames
  • Loading Data
Specific Objectives After completing this module, participants should:
  • Learn to work with R using RStudio
  • Learn to install packages and work will libraries in R
  • Learn the basic of programming in R
  • Learn tidyverse approaches to data manipulation

Beginner R2

This course will continue participants exposure to R focusing on visualizing, summarizing, tidying data. After completing this module, participants will be familiar with generating graphs with ggplot2 and aggregating, joining, and reshaping data using dplyr and tidyr.

 half-day in-classroom and additional online resources       Hybrid          $135


Key Topics
  • Visualization with ggplot2
  • Summarizing and joining with dplyr
  • Reshaping with tidyr
Specific Objectives After completing this module, participants should:
  • Learn to summarize (aggregate) and reshape data
  • Learn to join data frames (tables)
  • Learn to create visualizations (graphs)

Intermediate R3

This module will expose students to intermediate programming in R. Key topics include programming repetitive operations using loops and apply commands and writing functions. After completing this module, participants will be familiar with concepts for writing compact and efficient code for processing data.

 half-day in-classroom and additional online resources       Hybrid          $135


Key Topics
  • Loops
  • Vectorization
  • Apply commands
  • Writing functions
Specific Objectives After completing this module, participants should:
  • Know how to program iterative operations
  • Know how to write compact, reliable syntax
  • Know how to write functions for specific tasks

Intermediate R4

This module will introduce tidyverse methods for handling common but difficult to manage data types: text and geographic data. Key topics include working with text data using regular expressions and obtaining, manipulating, and visualizing geospatial data. After completing this module, participants will be able to apply their existing R skills to these complex data types.

 half-day in-classroom and additional online resources       Hybrid          $135


Key Topics
  • Functions for text data
  • Regular expressions
  • Geospatial data in ggplot2
  • Shapefiles and simple features geometries
Specific Objectives After completing this module, participants should:
  • Know how to use regular expressions
  • Know how to select, filter, and edit text data
  • Know how to plot geospatial data
  • Know how to obtain and use common shapefiles and census data