Course Description

So you want to learn R. Maybe you are looking to move to an advanced analytical role that requires it. Or you have found limitations to the type of operations you want to perform in Excel.

Perhaps you have tried books or online courses to learn R and found them unhelpful. It was like they were speaking a different language – and they were. Because this is probably your first time programming.  

The easiest way to learn something new is to make connections with something you already know.

That is why this course specifically frames learning R with the needs and experiences of Excel users in mind.

Who is this course for? 

  • Professionals who analyze data in Excel and want to augment their skill base
  • Those looking to speed up or automate advanced statistical techniques
  • Analysts looking for a free program for sophisticated data visualizations 

 No prior programming experience is required. As an Excel user, you know more than you think about programming, and this knowledge is the basis for learning R. 

I will take the features that you know and love in Excel, and reproduce them in R. This way you begin to see the similarities and differences between the programs, and know which tool to turn to given your unique circumstances. 

Topics covered

An Introduction to R

Here you will get a brief overview of R and download it to your machine. At its core, R is a statistical programming language. We start off with basic operations that should look very familiar to you as an Excel user. Plus, we begin to explore the open-source universe of R packages.

Getting Started in RStudio

RStudio is a wildly popular integrated development environment (IDE). In this unit I take you on a tour of RStudio, explaining just what is so "integrated" about it. Here our operations in R begin to diverge from Excel as the concept of the R object comes into play.

Getting Started with Objects

Objects are largely what make R, R. We will look at how to assign and explore objects.

Getting started with vectors

Similar to the cell in Excel, vectors are foundational to computing in R. Here we delve into the basics of vectors.

Reading, Writing and Exploring Data

Unlike Excel, data in R usually comes to us from external sources, like .csv or .txt files (and yes, Excel files!). In this unit we look at reading and writing data to and from R.  

So your dataset is in R. Now what? We cover some basics of exploratory data analysis as well.

Getting Started with Data Frames

Data Frames are a dominant structure for data analysis in R. In this lesson we explore the similarities between the R data frame and the Excel table and what this means for data frame management.

More Data Frame Manipulation

Data analysts spend a majority of their time cleaning datasets. This units provides tools for R data wrangling, many from the dplyr package.

Many of these operations will be familiar to you as an Excel user. We even cover R's equivalent of The Big Two in Excel...  VLOOKUP and PivotTables.

Advanced Dimensions and Data Types

As a statistical programming language, R has advanced data structures which you might not commonly use, but your Excel intuition might have something to say about. In this lesson we look at arrays, matrices and lists. 

Advanced Programming Topics

If you've used VBA you might know about user-defined functions and loops. We will cover the equivalents in R. We will also look at the apply family of functions -- a preferred alternative to looping in R.

Data Visualization

Humans are innately visual. In this unit we look at some of the most common ways to plot data in R.

Conclusion & Next Steps

Congratulations! It's time to take off the training wheels. In this unit, some tips for getting help and some favorite resources before you hit the open "R"oad for yourself.


Each lesson will be delivered over video usually in ~5 minute segments. As much as possible I will put R concepts into the context of an Excel user's needs and experiences. 

What makes this course different from others about R?

  • As much as possible, I frame lessons in the context of your background using Excel.
  • The course is designed with the corporate data analyst in mind, not the professional statistician. Walk before you can run -- we will not be covering advanced statistical concepts in this course, only how to organize, manipulate and visualize data using Excel as the jumping-off point.
  • No jargon. While I do use the textbook terms for R concepts, I try to bring them down to earth in concepts you will understand. I teach with the possibility in mind that this might be your first time programming.

Course Bonuses

Bonus #1: Companion Files in R and Excel – Yours to Download

You will be able to download all Excel and R files used in this course.  

Feel free to follow along with your own workbooks and scripts. These companion files will make it easy to check and compare your work.

Bonus #2: Lifetime Access to an Easy-to-Use Site

The course site is powered by Thinkific, a leading online course platform. It tracks your progress so you are able to come back right where you left off. This keeps you organized lets you focus on the learning.

You can access the course anytime, from any device. Continue the course from your computer, tablet or smartphone of any platform.

Bonus #3: Discussion Board for Every Module

Each module of the course has a discussion section. Ask questions and learn from other users in the comments. I will be here answering your questions and helping you along the way.

How Much Does The Course Cost?

Right now you can get lifetime access to the R Explained for Excel Users course for $249 $199 (save $50).

This is an online video course, which means you can watch the videos anytime you want, in the comfort of your own home or office.

There's no risk with my 30-day Money-Back Guarantee

I believe this is the best course on R for Excel users on the market. But if you are not satisfied with the product, I will gladly offer a refund within 30 days of purchase. Please contact me at for more information.

Disclaimer: This course is presented for information purposes only. Not all individual situations are the same and individual results will vary. Thus no guarantees can be made.

Microsoft Excel is a registered trademark of Microsoft Corporation.

Analyst, Educator and Consultant at

George Mount

Armed with a liberal arts degree and a master’s from a leading business school, I set out into the world to become an amazing analyst. Over the past few years I have worked on projects ranging from Canadian retailing to neurosurgeon compensation. Through this experience, I’ve noticed patterns of what makes a good analyst. Specifically, I’ve seen the best and worst in Microsoft Excel and data analysis. My online training is meant as a resource for recent grads and others who want to advance their career through Microsoft Excel, data analytics, and business economics.I've been featured on Excel TV, the Smart Data Collective, Brazen Careerist, and other blogs about business analytics and career development.

Course curriculum

  • 1


    • Welcome, Objectives & Prereqs

    • About Me... and About You

    • How to use this site


    • Welcome & Introductions

    • Resources

  • 2

    Getting Started with R

    • An Introduction to R

    • Installing R

    • Basic Operations

    • Special Values

    • Testing Conditions

    • Functions

    • Base R and R Packages

    • Resources

    • Discussion

  • 3

    Getting Started with RStudio

    • Downloading RStudio

    • Getting oriented in RStudio

    • Working in the console

    • Working in the script editor

    • Working in the files, plots, packages, help pane

    • Working in the environment and history pane

    • Customizing RStudio settings

    • Resources

    • Discussion

  • 4

    Getting Started with Objects

    • Assigning objects

    • Basic data types

    • Inspecting data types

    • Resources

    • Discussion

  • 5

    Getting Started with Vectors

  • 6

    Reading, Writing and Exploring Data

    • Introduction

    • Reading and writing .RDS files

    • Working with directories

    • Reading and writing .CSV files

    • Reading and writing .TXT files

    • Reading and Writing Excel Files

    • Reading and Writing Excel Files, Continued

    • Common pitfalls reading in data

    • A sneak peek at your data

    • More functions for data exploration

    • Resources

    • Discussion

  • 7

    Getting Started with Data Frames

    • Up and running with data frames

    • R data frames and Excel tables

    • Data frame creation

    • Appending to a data frame

    • Indexing and creating columns

    • Indexing elements of a data frame

    • Removing columns of a data frame

    • FIltering rows of a data frame

    • Deleting duplicate and incomplete rows in a data frame

    • Resources

    • Discussion

  • 8

    More Data Frame Manipulation

    • Getting Started with the Lahman Baseball Dataset

    • Up and running with dplyr

    • dplyr::rename

    • dplyr::filter

    • dplyr::arrange

    • dplyr::select

    • dplyr::mutate

    • dplyr::summarise

    • %>% (piping)

    • Approximate lookups with the cut function

    • PivotTables with reshape2

    • VLOOKUP with the merge function

    • Join types and the merge function

    • Resources

  • 9

    Advanced Data Structures and Dimensions

  • 10

    Advanced Programming Topics

    • User-defined functions

    • For loops

    • While loops

    • Repeat loops

    • The apply function

    • The lapply and sapply functions

    • The mapply function

    • Resources

    • Discussion

  • 11

    Data Visualization

    • Histograms

    • Dot plots

    • Bar charts

    • Line charts

    • Box plots

    • Scatter plots

    • ggplot2

    • Resources

    • Discussion

  • 12

    Next steps

    • Further Resources

    • Five Ways to Get Help in R

    • Goodbye

    • Discussion

    • Resources


5 star rating

A great introduction to R

Robert Sheu

As a PhD student, using statistics are an important part of my research. George's R course was a great introduction to using R. As a new R user, his course w...

Read More

As a PhD student, using statistics are an important part of my research. George's R course was a great introduction to using R. As a new R user, his course was very helpful as it explains the different parts of the statistics software clearly. Overall, this online course is a great guide for Excel users who would like to have some basic knowledge about using R.

Read Less
5 star rating

Rahim Zulfiqar Ali