If you want to know how you can learn R with R Swirl in R, you’ve come to the right place. Learning with R swirl, one can understand R Programming easily which is one of the key things to do in your journey as a data scientist today. There’s no doubt that without programming, you cannot become a data scientist. The power that programming holds with customizable analysis, and in-depth diagnosis of problems with predictive analysis is second to none. In today’s digital era, learning is democratized and accessible at no cost to everyone.
A simple google search can teach you everything that possibly a college classroom cannot today. Everything is on the internet for a curious person.
What is R Programming?
R programming first appeared in the year 1993, founded by Ross Ihaka and Robert Gentleman, and is widely used today as the 11th most popular programming language as of Mar’22 for purposes such as data mining, statistical analysis, and modeling along with highly customizable data visualizations. In the world of data science, it is taken to be a more statistically-biased competitor to Python.
Also, read -> How to choose your first programming language?
A simple introduction to R Swirl
In the year 2014, when Coursera first launched the Data Science Specialization (link provided below) put together by the Johns Hopkins University with professors Roger Peng, Brian Caffo, and Jeff Leek, that was the same moment when the world was introduced to Swirl. The course depended heavily on R Swirl to ensure that students could learn R programming as required for the course right from the R Console and for no extra cost.
The specialization comes with 10 courses for students to learn from. Use the link given to check them out.
Link here -> Coursera Data Science Specialization (Johns Hopkins University)
The Coursera course for data science by them was no doubt one of the most in-depth statistical courses that put forth statistical analysis including inferential statistics to the world and with a way to learn it interactively using ‘R Swirl’.
What does Learning with R Swirl offer students today?
As you can see in the image above, the R swirl course repository has a lot to offer to students for free learning today with courses like:
- Data Analysis
- Getting and Cleaning Data
- Mathematical Biostatistics Bootcamp
- Open Intro
- R Programming
- Regression Models
- Statistical Inference and more
The full course repository is maintained on GitHub and can be accessed here: R Swirl Course Repository
All R needs is your name and your email address if you are enrolled in a Coursera course and you can start learning R in R immediately.
How to Install R Swirl on your system?
Let us go over the steps required in order to install R Swirl in R studio. This is assuming that you already have R and R Studio installed.
R can be downloaded from here: R Project
R Studio can be installed from here: Download R Studio
Step 1: Download R
Step 2: Install R Studio
Step 3: Run R Studio on your system
Step 4: Type the code below in the R Console to install R Swirl
Step 5: Start Learning with R Swirl and follow the instructions interactively
Step 6: Install a course (choose from the GitHub course repository or find more open-source courses here: Swirl Courses)
Fun Fact: If you are interested to create your own interactive course on R Swirl and present it to the world you can do that too by installing Swirl and Swirlify on R Studio. Follow the instructions here to make your own course! -> Become a Swirl Instructor and Teach
Learning a programming language might seem like a difficult thing to do in the beginning and that’s when interactive learning and learning from online courses come into the picture. In today’s world, considering the boom of Data Science, there is a course for every single aspect of Data Science and free education is being provided to everyone to bridge the gap between the talent shortage and the high demand for capable data scientists who can use data to make the world a better place.
Try out interactive learning with R Swirl and learn R from anywhere and at any time. Let us know if you find this type of learning better than the rest!
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