Data Science and Machine Learning jobs are in high demand in this era of artificial intelligence. Students and professionals are becoming more interested in learning the R programming language when seeking high-paying tech jobs. Unquestionably, it is the most widely-used programming language among data scientists around the world.
As a result of its rapid and incessant growth, it is now the dominant tool for machine learning, data analysis, and statistical research. Many data science jobs are being generated every day due to the rise of big data, and knowing R programming will help you advance your career as a data scientist.
If you’re interested in a job in data science or statistics, a course in R should be on your list. Take an introductory course to learn the basics of this popular programming language and add it to your portfolio. It is easy to obtain an official Certificate of Completion once you have completed this R certification course. It is a terrific way to share your accomplishments with the world. The R programming language is described here for individuals who are unfamiliar with it.
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About R course
In recent years, R has become increasingly popular among data analysts. You may download it for free and use it on various platforms, including Windows, macOS, and Unix. As a result, new statistical procedures can be programmed in a simple and basic way. There are several excellent R programming courses offered by the training providers, including an introduction to R programming that includes data types, data structures, control statements, and more, as well as hands-on exercises for each.
Why Use R?
There are mainly four reasons given in the course, which are:
- Popularity: Statistical analysis is at the core of R’s capability. With the Data Science boom, it has become a top language for data scientists.
- Free and open-source: It’s open-source and free to use, like most languages. R is a beautiful alternative to expensive statistical software like IBM SPSS.
- Extensive functionality: R has a wide range of applications. Besides statistics and graphing, there are numerous other features, including creating websites, analyzing language, and many others. You may accomplish nearly any task with the appropriate package.
- Huge community: It is open-source and includes a wide variety of packages to extend capabilities. As a result, you’ll be able to seek support from the forums you run into a problem with R.
How to learn R programming?
In particular, if you don’t have any programming expertise or are more comfortable with statistical software than a simple programming language, learning R can be challenging.
There are many excellent (free) materials on R available, but regrettably, you could include not all of them here. We believe there is a mix of documentation, online courses, books, and more—the ideal way to get you up and running with R as quickly and efficiently as possible.
You should use them in conjunction with one another to help you master the most powerful statistical language in the world!
- Watch instructive videos: It’s impossible to study R in a single day. But if you follow the appropriate procedures, you can learn it in 2 weeks. You may find many video tutorials on R on the internet. However, you must use caution when selecting the videos. If you choose a more advanced video first, you may become confused. As a result, make sure you’re watching quality videos that are appropriate for your skill level.
- Online courses in R programming and R tutorials: Free R tutorials and courses abound on the internet. Still, most of them are neither complete nor up-to-date, making them unusable. There are only a few free courses and tutorials that are of outstanding quality. Learners will find several good R tutorials, which are part of a statistics or data science program. This course lets you learn the fundamentals of R, including factors, lists, and data frames. Upon completing this course, you’ll be able to do your first data analysis on your own. In 2012, Oracle claimed over 2 million R users globally, solidifying R’s position as a primary programming language for statistics and data science. About 40 percent of R users increase every year, and many companies use it in their everyday tasks.
Use R code and libraries to generate spectacular data visualizations using the major R data structures. Coding tasks that are engaging and interactive strengthen your knowledge through real-world activities in this course.
- Follow blogs: On the web today, you’ll find a solid selection of the most excellent R-related blogs to follow. You won’t have any trouble locating an article on the specific topic or use case you’re interested in because there are so many blogs that are curated by one person alone!
- Read books: Books often get a bad rap because you can access most programming concepts online for free. Sure, if you’re only going to use the book as a reference, you’d be better off saving your money and using Google search instead. In contrast, working through an entire book at the foundational level will provide an excellent level of understanding if you’re a beginner.
- Experiment: Once you’re comfortable with the syntax and principles of R, you can experiment to learn and enhance your understanding of R programming. New strategies and procedures are emerging with R because it is a dynamic language.
However, don’t limit yourself to only these methods and recommendations. Identifying frequent R pitfalls and learning how to avoid them is crucial as you gain experience.
Jobs in R programming
In the domains of statistics and data analysis, R programming abilities are required for thousands of professions. Any data specializations requiring mastery of statistical techniques will benefit from adding R coding language abilities to your resume.
Summary
Learn how to learn R programming in this post. If you know how to learn R, it’s a fun language. You must correctly set up the R environment before you begin programming. Then, master the basics of syntax and eventually start working on your projects and assignments. An excellent online course, on the other hand, is unbeatable. As a result, it is better to enroll in online courses.
