10 Best R Programming Courses On Udemy

When it comes to Data Science, R is the most widely used programming language. It is often used to analyze both structured and unstructured data. This is the reason R has become the standard language for statistical procedures.

R has several features that distinguish it from other Data Science languages. A handful of the many appealing features of the R programming language are readily apparent.

It’s well-maintained, has solid connectivity to various data and other systems, and is adaptable enough to tackle challenges across a wide range of fields.

Also Read: How To Learn Data Science [Beginner’s Guide]

10 Best R Programming Courses on Udemy

Udemy is one of the best platforms for learning online. The best part is that the courses are affordable, and the quality is top-notch as experience professionals share their expertise.

With over 32,000 courses taught by 18,000 instructors, you can explore courses on various topics such as programming, UX design, video editing, and many others. Here, we will explore the ten best courses on R programming that can help you kickstart your career as a data scientist.

Do check out all these courses to make an informed decision. So, without further ado, let’s get started.

1. Data Science and Machine Learning Bootcamp with R

Rating: 4.7

Number of Students: 72,462

Instructor: Jose Portilla

About Instructor: Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science and programming.

This course is appropriate for beginners with no prior programming expertise and experienced developers who want to transition to Data Science. This course is equivalent to other Data Science Bootcamps.

The only difference is that they cost thousands of dollars, but you can study everything for a fraction of the price in this course. This is one of the most comprehensive data science and ML courses on Udemy. It has over 100 video lectures in HD quality.

Course Content:

• Windows, macOS, and Linux installation set-up.
• Introduction to R basics
• R Matrices
• R Data Frames
• R Lists
• Data Input and Output with R
• R Programming basics
• Data visualization and manipulation with R
• Data visualization project
• Interactive visualizations with Plotly
• Capstone data project
• Introduction to machine learning with R

Also Read: 15 Best Python Libraries for Data Science and Analysis

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

Rating: 4.7

Number of Students: 51,766

Creator: Kirill Eremenko

About Course Instructor: Professionally, he comes from the Data Science consulting space with experience in finance, retail, transport, and other industries. The best analytics mentors trained him at Deloitte Australia and started on Udemy.

One of the best R courses on Udemy, this course offers professional R video training, innovative dataset designs, and exciting and engaging tasks that give you a taste of real-world analytics.

After completing each program, you will have a robust set of abilities to take with you into your Data Science job.

Course Content

• How to use lists.
• Prepare Data for analysis.
• How to use apply(), lapply(), and sapply() functions instead of loops
• How to nest apply(), lapply(), and sapply() functions within each other

Also Read: 10 Best Data Science Coursera Courses For Beginners

3. R Programming for Absolute Beginners

Rating: 4.6

Number of Students: 147,60

Creator: Bogdan Anastasiei

About Instructor: He is an assistant professor at the University of Iasi, Romania, Faculty of Economics and Business Administration.

As a first step toward becoming a skilled R data scientist, this course will help you grasp the basics of R in a short amount of time. The course is designed for complete beginners, so you don’t need any prior knowledge of R to begin.

You will have the most crucial R programming skills after completing this course, and you will be able to further expand these skills by practicing what you have learned in the course.

This course is divided into nine sections and has approximately 100 video lectures. You’ll learn the following concepts after this course.

• Work with vectors, matrices, and lists.
• Work with factors
• Manage data frames
• Write complicated programming structures (loops, conditional statements)
• Create your functions and binary operations
• Work with strings

Also Read: What Is a Business Intelligence Analyst?

4. Statistics for Data Analysis Using R

Rating: 4.6

Number of Students: 7,986

Creator: Sandeep Kumar

About Instructor: Sandeep Kumar has more than 35 years of Quality Management experience. He has worked as Quality Director on several projects, including Power, Oil and Gas, and Infrastructure projects.

This course will teach you the fundamentals of statistics and data analysis. It also aids in applying these principles using a variety of examples and data sets.

The following are some of the things you will learn:

• Mean, Mode, Median, Quartile, Range, Inter Quartile Range, and Standard Deviation are all descriptive statistics.
• Three charts for data visualization: histogram, box & whisker plot, and scatter plot.
• Basic Concepts, Permutations, and Combinations in Probability
• Basic theoretical principles in population and sampling
• Probability Distributions R functions and the visualize package
• ANOVA – Perform Analysis of Variance
• Hypothesis Testing – Samples – z Test, t-Test, F Test, Chi-Square Test (ANOVA)

Also Read: 11 Best Free Android Apps To Learn Data Science

5. Introduction to Time Series Analysis and Forecasting in R

Rating: 4.6

Number of Students: 10,960

Creator: R-Tutorials Training

This course created by R-Tutorials Training is the next in our list of best R courses on Udemy. The following are some of the things you will learn:

• Use R to perform calculations with time and date data
• Create models for time series data
• Use models for forecasting
• Identify models suitable for a given data
• Visualize time-series data
• Transform standard data into time-series format
• Clean and pre-process time series
• Interpret given models
• Know the best time-series libraries for a given problem
• Compare the accuracy of different models

Also Read: 10 Best Data Science Coursera Courses For Beginners

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

Rating: 4.5

Number of Students: 5,749

Creator: R-Tutorials Training

After completing this course, you should establish filters and columns in tables, generate plot parameters, and focus on specific sections of plots.

The following are some of the things you will learn:

• Create multi-page shiny apps
• Add focus and zooming features to shiny apps
• Develop shiny applications based on data tables
• Use pre-defined layouts for style
• Generate downloadable tables

Also Read: 10 Best Books On Data Science For Beginners [2021]

7. R Tidyverse Reporting and Analytics for Excel Users

Rating: 4.6

Number of Students: 5,260

Creator: Jonathan Ng

Next in our list of best R courses on Udemy, this course will benefit anyone who uses Excel for reporting or analysis.

You may use it to make day-to-day Excel reporting and analytics much faster and easier without requiring any complicated statistical approaches while also providing a solid base to develop into such areas.

This course employs the Tidyverse R standards, which give a single, complete, and easy-to-understand technique for using R without various methods.
The following are some of the things you will learn:

• Working Directories and R Projects
• Loading Data
• Using the mutate function to create and alter computed columns in our datasets
• Filtering
• Compacting Data
• Getting a general picture of our data
• Creating visualizations
• Reporting

Also Read: Getting Started With PySpark on Ubuntu with Jupyter Notebook

8. R Data Pre-Processing & Data Management

Rating: 4.5

Number of Students: 4,143

Creator: R-Tutorials Training

This course covers the basics of importing CSV files, keeping your data organized, querying and filtering (you’ll need to filter for the required parameters if you have an extensive database), integrating and communicating with SQL, and outlier identification.

The following are some of the things you will learn:

• Select and implement a proper object class (data. frame, data. table, data frame)
• Convert your data into a tidy format
• Filter and query the data
• Join two data tables together using dplyr 2 table verb syntax
• Use SQL code within R

Also Read: Introduction to Data Analysis and Visualization with Excel

9. Species Distribution Models with GIS & Machine Learning in R

Rating: 4.3

Number of Students: 2,259

Creator: Minerva Singh

About Course Instructor: She completed a Ph.D. (University of Cambridge, UK) in 2017, where she focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems.

This course will teach you how to use R to implement some of the most popular machine learning algorithms using real-world ecological data. Plus, you’ll get hands-on experience with a standard environmental modeling technique called species distribution modeling (SDM), which uses real-world data.

You’ll also learn to use R to simulate ecological systems using GIS and Machine Learning. These are all the things that made us include this course in our list of best R courses on Udemy.

Also Read: 10 Best Udemy Python Courses for Beginners

10. Survival Analysis in R

Rating: 4.8

Number of Students: 1,120

Creator: R-Tutorials Training

Statistics has a sub-discipline called survival analysis. It has several distinct names. This type of study is also known as event-time analysis, reliability analysis, or duration analysis.

Thanks to the survival package, R is one of the most used tools for performing this type of analysis. This course will teach you how to perform survival analysis using R.

The following are some of the things you will learn:

• The fundamentals of survival analysis
• Survival analysis using R
• Determine which packages are optimal for survival data.
• Estimator Kaplan-Meier
• Logrank test
• Model of Cox proportional hazards
• Parametric models
• Trees for survival
• Imputation of missing data
• Detecting outliers

Also Read: How To Create Keylogger In Python

Verdict

With this, we sum up our list of the ten best R programming courses on Udemy. Explore all these courses and check out their overall rating to make an informed decision. Based on your learning goals, we have added courses suitable for beginners and experts.