TOP 10 Most Popular R Courses

TOP 10 Most Popular R Courses

TOP 10 Most Popular R Courses

  • 1. Python & R Programming
  • 2. Data Manipulation With Dplyr in R
  • 3. R for Beginners
  • 4. R Programming A-Z™: R For Data Science With Real Exercises!
  • 5. 2021 Data Science & Machine Learning with R from A-Z Course
  • 6. R Shiny Interactive Web Apps - Next Level Data Visualization
  • 7. R Programming: Advanced Analytics In R For Data Science
  • 8. Statistics with R - Intermediate Level
  • 9. Maps with R Leaflet
  • 10. R for Data Science: R Programming Bootcamp

1. Python & R Programming

Python & R Programming
Python & R Programming
Learn the two most widely used programming languages with Data Science: Python and R

Description

Both Python and R are popular programming languages for Data Science. While R’s functionality is developed with statisticians in mind (think of R's strong data visualization capabilities!), Python is often praised for its easy-to-understand syntax.

Ross Ihaka and Robert Gentleman created the open-source language R in 1995 as an implementation of the S programming language. The purpose was to develop a language that focused on delivering a better and more user-friendly way to do data analysis, statistics and graphical models.

Python was created by Guido Van Rossem in 1991 and emphasizes productivity and code readability. Programmers that want to delve into data analysis or apply statistical techniques are some of the main users of Python for statistical purposes.

2. Data Manipulation With Dplyr in R

Data Manipulation With Dplyr in R
Data Manipulation With Dplyr in R
A straightforward tutorial in data wrangling with one of the most powerful R packages - dplyr.

Description

Data manipulation is a vital data analysis skill – actually, it is the foundation of data analysis. This course is about the most effective data manipulation tool in R – dplyr!

As a data analyst, you will spend a vast amount of your time preparing or processing your data. The goal of data preparation is to convert your raw data into a high quality data source, suitable for analysis. More often than not, this process involves a lot of work. The dplyr package contains the tools that can make this work much easier.

3. R for Beginners

R for Beginners
R for Beginners
Introduction to Programming Language R. Tools for Data Science, Data Analysis and Statistical Analysis. RStudio.

Description

Are you one of the people that would like to start a data science career or are you just fond of using data for data analysis in your spare time or for your job?  Do you use spreadsheets for data cleaning, wrangling, visualization, and data analysis? I think it is time to enhance your hobby or your career path with learning adequate skills such as R.

4. R Programming A-Z™: R For Data Science With Real Exercises!

R Programming A-Z™: R For Data Science With Real Exercises!
R Programming A-Z™: R For Data Science With Real Exercises!
Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2

Description

Learn R Programming by doing!

There are lots of R courses and lectures out there. However, R has a very steep learning curve and students often get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.

After every video you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

5. 2021 Data Science & Machine Learning with R from A-Z Course

2021 Data Science & Machine Learning with R from A-Z Course
2021 Data Science & Machine Learning with R from A-Z Course
Become a professional Data Scientist with R and learn Machine Learning, Data Analysis + Visualization, Web Apps + more!

Description

Welcome to the Learn Data Science and Machine Learning with R from A-Z Course!

In this practical, hands-on course you’ll learn how to program in R and how to use R for effective data analysis, visualization and how to make use of that data in a practical manner. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language.

Our main objective is to give you the education not just to understand the ins and outs of the R programming language, but also to learn exactly how to become a professional Data Scientist with R and land your first job.

The course covers practical issues in statistical computing which include programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting on R code. Blending practical work with solid theoretical training, we take you from the basics of R Programming to mastery.

6. R Shiny Interactive Web Apps - Next Level Data Visualization

R Shiny Interactive Web Apps - Next Level Data Visualization
R Shiny Interactive Web Apps - Next Level Data Visualization
Learn how to use R and Shiny to create compelling data visualizations and how to share them online.

Description

R shiny allows you to present your data interactively – that means your app users can:

  • Set filters and columns in tables
  • Generate parameters for plots
  • Zoom and focus on specific areas of plots
  • Focus on selected portions of your data
  • Provide or upload files, text and all sorts of data
  • And much more

App users can do all of this without any R knowledge. You do the coding, your users get the info they are looking for!

In this course I will show you step by step how to master R Shiny. We will start out with the general shiny script – all scripts should have the same basic structure.

7. R Programming: Advanced Analytics In R For Data Science

R Programming: Advanced Analytics In R For Data Science
R Programming: Advanced Analytics In R For Data Science
Take Your R & R Studio Skills To The Next Level. Data Analytics, Data Science, Statistical Analysis in Business, GGPlot2

Description

Ready to take your R Programming skills to the next level?

Want to truly become proficient at Data Science and Analytics with R?

This course is for you!

Professional R Video training, unique datasets designed with years of industry experience in mind, engaging exercises that are both fun and also give you a taste for Analytics of the REAL WORLD.

In this course you will learn:

  • How to prepare data for analysis in R
  • How to perform the median imputation method in R
  • How to work with date-times in R
  • What Lists are and how to use them
  • What the Apply family of functions is
  • How to use apply(), lapply() and sapply() instead of loops
  • How to nest your own functions within apply-type functions
  • How to nest apply(), lapply() and sapply() functions within each other
  • And much, much more!

The more you learn the better you will get. After every module you will already have a strong set of skills to take with you into your Data Science career.

8. Statistics with R - Intermediate Level

Statistics with R - Intermediate Level
Statistics with R - Intermediate Level
Statistical analyses using the R program

Description

If you want to learn how to perform the most useful statistical analyses in the R program, you have come to the right place.

Now you don’t have to scour the web endlessly in order to find how to do a Pearson or Spearman correlation, an independent t test or a factorial ANOVA, how to perform a sequential regression analysis or how to compute the Cronbach’s alpha. Everything is here, in this course, explained visually, step by step.

So, what will you learn in this course?

First of all, you will learn how to perform association tests in R, both parametric and non-parametric: the Pearson correlation, the Spearman and Kendall correlation, the partial correlation and the chi-square test for independence.

The test of mean differences represent a vast part of this course, because of their great importance. We will approach the t tests, the analysis of variance (both univariate and multivariate) and a few non-parametric tests. For each technique we will present the preliminary assumption, run the procedure and carefully interpret all the results.

9. Maps with R Leaflet

Maps with R Leaflet
Maps with R Leaflet
Transform your data into interactive maps!

Description

Leaflet.js is one of the most popular libraries for creating beautiful looking maps. Companies like Facebook, Pinterest, and The Washington Post use Leaflet to create maps that draw-in and engage viewers in a unique way.

In this course, we'll be using the Leaflet package for R to analyze FBI homicide data in the United States.

10. R for Data Science: R Programming Bootcamp

R for Data Science: R Programming Bootcamp
R for Data Science: R Programming Bootcamp
Learn R Programming Fundamentals, Data Wrangling, Data Visualization for Data Science

Description

Welcome to this course of R Programming for Beginners with the hands-on tutorial, and become an R Professional which is one of the most favoured skills, that employer's need.

Whether you are new to programming or have never programmed before in R Language, this course is for you! This course covers the R Programming from scratch. This course is self-paced. There is no need to rush - you learn on your own schedule. 

R programming language iѕ one of the best open-source programming language and more powerful than other programming languages. It iѕ well documented and has a clean syntax and quite еаѕу tо lеаrn.

This course will help anyone who wants to start a саrееr in Data Science and Machine Lеаrning. You need to have basic undеrѕtаnding оf R Programming to become a Data Scientist or Data Analyst.

This course begins with the introduction to R course that will help you write R code in no time. Then we help you with the installation of R and RStudio on your computer and setting up the programming environment. This course will provide you with everything you need to know about the basics of R Programming.