Do you want to learn data analytics with R? If yes, then Good Decision! Because R programming has various statistical and graphical capabilities. R has a huge variety of libraries to perform statistical analysis. Some most powerful visualization packages in R are ggplot2, ggvis, googleVis, and rCharts. So, if you are looking for a data analyst with R online courses, then this article will help you.
In this article, you will find the 9 Best Data Analyst with R Online Courses. And these courses are filtered out on the following criteria-
Criteria-
- Rating of these Courses.
- Coverage of Topics.
- Engaging trainer and Interesting lectures.
- Number of Students Benefitted.
- Good Reviews from various aggregators and forums.
So, without wasting your time, let’s start finding the Best Data Analyst with R Online Courses-
Data Analyst with R Online Courses
- 1. Data Analyst with R- Datacamp
- 2. Google Data Analytics Professional Certificate– Coursera
- 3. Data Analysis with R– Udacity
- 4. Statistics with R Specialization- Coursera
- 5. R Programming: Advanced Analytics In R For Data Science- Udemy
- 6. Statistical Analysis with R for Public Health Specialization– Coursera
- 7. Applied Statistical Modeling for Data Analysis in R- Udemy
- 8. Data Visualization & Dashboarding with R Specialization– Coursera
- 9. Statistician with R– Datacamp
- Conclusion
1. Data Analyst with R– Datacamp
Time to Complete- 77 hours
This is a career track by Datacamp. This career track teaches data analytics with R programming. There is a total of 21 courses on this career track. In the beginning, you will understand the basics of data analysis and R programming such as data structures, conditional statements, loops, etc.
Then you will learn the processes of data manipulation and visualization using the tools dplyr and ggplot2. You will also learn how to create and modify each element of an R Markdown file, including the code, text, and metadata.
This career track also covers the following topics- Data Manipulation with data.table in R, Joining Data with data.table in R, Importing Data in R, Data Cleaning in R, Exploratory Data Analysis in R, Statistics in R, Categorical Data in the Tidyverse, and SQL.
Who Should Enroll?
- Those who are beginner and want to learn Data analytics with R programming.
Interested to Enroll?
If yes, then check out the course details here- Data Analyst with R
2. Google Data Analytics Professional Certificate– Coursera
Provider- Google
Rating- 4.8/5
Time to Complete- 6 Months (If you spend 10 hours/week)
This is one of the most popular Data Analyst Certification programs and uses R Programming. In this program, you will gain an understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job and an understanding of data-driven decision-making and how data analysts present findings.
In this course, you will also learn how to prepare data for exploration and how analysts use spreadsheets and SQL with databases and data sets. Then you will learn how to check and clean your data using spreadsheets and SQL and how to verify and report your data cleaning results.
This course also covers how to perform complex calculations on your data to complete business objectives. You will learn about Tableau, a data visualization platform that will help you create effective visualizations for your presentations. At the end of this course, you will learn how to use RStudio to apply R to your analysis.
There are 8 courses in this certification program.
Courses Include-
- Foundations: Data, Data, Everywhere
- Ask Questions to Make Data-Driven Decisions
- Prepare Data for Exploration
- Process Data from Dirty to Clean
- Analyze Data to Answer Questions
- Share Data Through the Art of Visualization
- Data Analysis with R Programming
- Google Data Analytics Capstone: Complete a Case Study
Extra Benefits-
- You will earn a Shareable Certificate after completing the Data Science specialization Program.
- Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Those who are a beginner and want to gain data analytics skills using R programming.
Interested to Enroll?
If yes, then check out all details here- Google Data Analytics Professional Certificate
3. Data Analysis with R– Udacity
Time to Complete- 2 Months
This is a completely FREE course to learn data analysis using R programming. This course begins with the introduction of exploratory data analysis (EDA). Then you will learn R basics by installing RStudio and packages.
After that, you will perform EDA to understand the distribution of a variable and to check for anomalies and outliers. You will also learn how to quantify and visualize individual variables within a data set to make sense of a pseudo-data set of Facebook users.
In this course, you will work on the Diamonds and Price Predictions project. In this project, you will investigate the diamond data set and see how predictive modeling can allow us to determine a good price for a diamond.
Who Should Enroll?
- Those who have prior knowledge of statistics.
Interested to Enroll?
If yes, then check out the course details here- Data Analysis with R
4. Statistics with R Specialization– Coursera
Rating- 4.6/5
Provider- Duke University
Time to Complete- 7 Months (If you spend 3 hours/week)
This specialization program will give you in-depth Statistics knowledge with the help of R. In this program, you will learn how to analyze and visualize data in R and create reproducible data analysis reports, and much more.
R is much better than Python for performing statistical operations. So, if you want to master Statistics, then I would recommend this specialization program.
In this specialization program, you will learn the following skills- Bayesian Statistics, Linear Regression, Statistical Inference, R Programming, Statistics, Rstudio, Exploratory Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Bayesian Linear Regression, Bayesian Inference, and Model Selection.
This specialization program contains 5 Courses. Let’s see courses details-
Courses Include-
- Introduction to Probability and Data with R
- Inferential Statistics
- Linear Regression and Modeling
- Bayesian Statistics
- Statistics with R Capstone
Extra Benefits-
- You will get a Shareable Certificate and Course Certificates upon completion.
- Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Those who have basic math knowledge. No previous programming knowledge is required for this course.
Interested to Enroll?
If yes, then check out all details here- Statistics with R Specialization
5. R Programming: Advanced Analytics In R For Data Science– Udemy
Rating- 4.7/5
Time to Complete- 6 hours
This is another best course to learn data analytics using R programming. In this course, you will learn how to prepare data for analysis in R, how to perform the median imputation method in R, and how to work with date-times in R.
The instructor of this course Kirill is my favorite and explains each topic very clearly. In this course, you will also learn how to use apply(), lapply(), and sapply() instead of loops, how to convert date-times into POSIXct time format, and much more.
Extra Benefits-
- You will get a Certificate of completion.
- Along with that, you will get full lifetime access and 5 articles.
Who Should Enroll?
- Those who have basic knowledge of R, GGPlot2 package, dataframes, vectors and vectorized operations.
Interested to Enroll?
If yes, then check out the course details here- R Programming: Advanced Analytics In R For Data Science
6. Statistical Analysis with R for Public Health Specialization– Coursera
Rating- 4.7/5
Provider- Imperial College London
Time to Complete- 4 months (If you spend 3 hour/week)
In this specialization program, you will learn statistical thinking (types of variables, common distributions, hypothesis testing), linear regression, logistic regression, and survival analysis.
In linear regression, you will learn how to prepare the data, assess how well the model fits the data, and test its underlying assumptions. You will also get to know statistical concepts like sampling, uncertainty, variation, missing values, and distributions.
Throughout this program, you will get your hands dirty with analyzing data sets covering some big public health challenges such as fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalization using R programming.
There are 4 courses in this specialization program.
Extra Benefits-
- You will earn Shareable Specialization and Course Certificates.
- Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Those who are a beginner with no knowledge of statistics or R software.
Interested to Enroll?
If yes, then check out the details here- Statistical Analysis with R for Public Health Specialization
7. Applied Statistical Modeling for Data Analysis in R– Udemy
Rating- 4.2/5
Time to Complete- 9.5 hours
This course is good for understanding statistical techniques using R programming. In this course, you will learn how to use R programming to perform different statistical data analysis and visualization tasks for data modeling.
You will also learn to identify which statistical techniques are best suited to their data and questions. The instructor covers the implementation of linear modeling techniques, advanced regression analysis, and multivariate analysis.
Extra Benefits-
- You will get a Certificate of completion.
- Along with that, you will get full lifetime access, 3 articles, and 41 downloadable resources.
Who Should Enroll?
- Those who have prior knowledge of R and R Studio.
Interested to Enroll?
If yes, then check out the course details here- Applied Statistical Modeling for Data Analysis in R
8. Data Visualization & Dashboarding with R Specialization– Coursera
Provider- Johns Hopkins University
Rating– 4.9/5
Time to Complete- 4 months (4 hours per week)
This specialization program is good for those who want to learn data visualization using R. In this program, you will learn how to use ggplot2 to make a variety of visualizations and to polish those visualizations using tools within ggplot.
You will also learn how to import data into R, manipulate that data using tools from the popular tidyverse package, and make simple reports using R Markdown.
This specialization program will also teach you how to create interactive visualization using Shiny, as well as combining different kinds of figures made in R into interactive dashboards. In this specialization program, there are 5 courses.
Courses Details-
- Getting Started with Data Visualization in R
- Data Visualization in R with ggplot2
- Advanced-Data Visualization with R
- Publishing Visualizations in R with Shiny and flex dashboard
- Data Visualization Capstone
Extra Benefits-
- You will earn Shareable Specialization and Course Certificates.
- Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Those who are a beginner and want to learn Data visualization using R programming.
Interested to Enroll?
If yes, then check out the details here-Data Visualization & Dashboarding with R Specialization
9. Statistician with R– Datacamp
Time to Complete- 108 hours
This is a Career Track offered by Datacamp. In this career track, there are 27 courses. This career track will help you to gain essential skills to land a job as a statistician. In this career track, you will learn basic to advanced level concepts of statistics.
At the beginning of the career track, you will learn how to collect, analyze, and draw accurate conclusions from data, concepts of random variables, distributions, and conditioning, using the example of coin flips, how to fit simple linear and logistic regressions, how to fit model binomial data with logistic regression and count data with Poisson regression, etc.
Then you will learn Sampling, Hypothesis testing, basic experimental design, A/B testing, how to deal with missing data, survey design, survival analysis, Bayesian data analysis, Factor Analysis, and much more.
Who Should Enroll?
- Those who have previous knowledge in R programming.
Interested to Enroll?
If yes, then check out all details here- Statistician with R
And here the list ends. I hope these data analyst with R online courses will definitely help you to learn data analytics with R Programming. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.
Conclusion
In this article, I tried to cover all the Best data analyst with R online courses. If you have any doubt or questions, feel free to ask me in the comment section.
All the Best!
Enjoy Learning!
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Written By Aqsa Zafar
Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.