If you’re getting started with data analysis and have to work on your first big statistics projects, R is a tool that you’ll need to master. Learning to work with a new programming language can be both fun and challenging. With DataCamp R courses, you can immerse yourself in quality education that won’t get boring.
But let’s take a few steps back first – what makes R such a popular choice among data analysts? Today, we’ll take a look at this programming language and where it might come in handy. Don’t worry, it won’t get too techy – we’ll simply look over the basics without getting into the code itself.
Then we’ll discuss why DataCamp R courses are a great option if you’re just starting out. Spoiler alert: DataCamp offers gamified education with opportunities to get coding practice as you’re learning, whether you’re a beginner or simply want to put your programming chops to the test.
Finally, you’ll get to learn about the DataCamp R Programming skill track that will take you from zeRo to masteR in no time. And if you find yourself wanting to learn more about the platform itself first, you can read our DataCamp review here.
Without further ado, let’s start learning about R with DataCamp.
Table of Contents
Why Should You Choose DataCamp R Courses?
If this is your first venture into working with R, you might want to have some basics covered to understand what it is and where you might need to use it. Firstly, R is not just a programming language – it’s also a software that data scientists use for statistical analysis.
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So, if you need to do some data mining, conduct analysis, or work with stats, R is the tool you’ll be using almost exclusively. In fact, it’s one of the most popular programming languages among statisticians. R is also among the most-used programming tools in the world[1].
R has been around for around 30 years by now. It’s no wonder that there’s a massive community of useRs – the term used to describe R programmers – all around the globe. They’ve gathered numerous resources, tutorials, guides, and courses to help newcomers master the art of R.
One of such tools for beginner statisticians is the wide selection of DataCamp R courses. DataCamp is a digital learning platform dedicated to helping new data scientists and analysts become experts in their fields.
To ease you into the world of R, DataCamp offers a beginner-friendly R Programming skill track. It was curated to provide you with the best experience of building up your skill set. The five-course track covers the essentials of R, from the very basics of data analysis to writing your own code from scratch.
We’ll be taking a closer look at the five courses in the DataCamp R Programming skill track. Starting with the DataCamp Introduction to R course, we’ll move on to the more intermediate skills, like how to write your code efficiently and how object-oriented programming with R works.
And don’t worry – you won’t be required to install additional software to access the materials. Everything will be presented to you in DataCamp’s virtual learning environment. So, you’ll be able to access your classes and complete the assignments on your desktop or mobile device without leaving the DataCamp website or app.
So, it’s finally time to begin your jouRney into data analysis.
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Introduction to R (Enroll Here)
- Offered by: Jonathan Cornelissen
- Duration: 4 hours
- Price: FREE
- Certificate: No
- Level: Beginner
- Where to apply? HERE
Let’s get the basics covered first. You know where R is useful, and you’re ready to start learning. Let’s take our first step into the R Programming skill track – the Introduction to R course. If you’ve had little to no experience working with R up to this point, it’s the perfect place to begin.
Introduction to R is one of DataCamp’s biggest courses, with over 2 million learners. It’s one of the platform’s staples. According to DataCamp R reviews, the introductory course is comprehensive, easy to follow, and well-balanced for newcomers who may have never coded before in their lives.
This four-hour course is structured into six classes, known as chapters. But don’t worry – it won’t get overwhelming. You’ll get videos explaining the ins and outs of R, examples of where you can use the things you’re learning in code, and even some hands-on experience to get you started.
Throughout the DataCamp Introduction to R course, you’ll be covering the essentials, such as:
- The basic data types used in R;
- Creating and using vectors;
- The use and importance of matrices;
- Creating and comparing factors;
- Storing datasets in data frames;
- Creating and subsetting lists.
By the end of the course, you’ll be able to conduct a simple research project using real-life data. To really set your analytical skills in stone, you’ll have the opportunity to work on over 60 exercises during the course itself.
And if you find yourself looking for a bigger challenge, you can take a glimpse into DataCamp Projects – a way to put your brand-new skills to the test and see how R research works in the real world. Some of the DataCamp R projects are even available for free, and we’ve covered a couple of them here.
The Introduction to R course is taught by Jonathan Cornelissen, one of the co-founders of DataCamp. Jonathan brings his passion for digital education and his years of expertise working with R into this course, creating a solid learning environment for beginners.
If you have doubts about the quality, all you have to do is take a look at what some of the learners have to say. As far as DataCamp R reviews are concerned, the intro class, as well as the other courses on the R Programming track, offer high-quality materials and insightful advice that’s easy to follow even for the greenest learners.
You might be wondering: how much does the DataCamp Introduction to R course cost? Nothing. This is one of the six DataCamp courses you can access completely for free, allowing you to start learning as hassle-free as possible.
Of course, if you find yourself wanting to stay on the DataCamp R Programming skill track, you can join the Premium subscription plan for $25/month. This will allow you to access the entire DataCamp catalog with over 350 courses. So, you can even test the waters of other languages, like Python or SQL.
Intermediate R (Enroll Here)
- Offered by: Filip Schouwenaars
- Duration: 6 hours
- Price: from $25/month
- Certificate: No
- Level: Intermediate
- Where to apply? HERE
Now that you understand the fundamentals of working with R, you can start looking into some of the more complex concepts. Don’t worry, you won’t be jumping straight into dark waters. Thanks to the structure of the DataCamp R Programming skill track, you can keep your progress steady and cover all new features step-by-step.
The Intermediate R course is the next stage of your venture into the world of R. Things will get a bit more technical, but don’t worry – it won’t be too complex. The course is designed to immediately follow the DataCamp Introduction to R course, so you won’t be lost in the woods.
This course is six hours long and it’s full of hands-on experience. Alongside guiding videos, tips and tricks, and fun facts about using R, you will get to try out more than 80 exercises. You’ll work on practical tasks and even have a hand at writing parts of the code yourself.
You’ll be covering five chapters in this course:
- Conditionals and Control Flow
- Loops
- Functions
- The Apply Family
- Utilities
You’ll start off by learning how to use two different types of operators – relational and logical. You’ll need them to compare R objects and combine TRUE/FALSE values.
Then, you’ll go through the whole process of working with loops. You’ll get to figure out each element by yourself with the task of writing a loop from scratch. If you feel lost, you can check out one of the DataCamp R cheat sheets to help you out.
The next chapter covers one of the most fundamental elements in programming – functions. Here, you’ll get to work with R-specific functions (and see just how many R-based puns it’s possible to make in the course titles).
The fourth chapter circles back to the loops. You’ll see how you can optimize your code with apply functions and turn the process of programming from strictly mechanical to intuitive. This chapter will also cover different variants of apply, like sapply and vapply.
The final section will help you figure out how to best leverage R to make programming simple and effective. You’ll familiarize yourself with a number of functions and utilities that will help you work with times and dates in your statistical projects.
Congrats, your R skills are now at an intermediate level! While I can’t give you a gold star sticker, you will earn almost 7000 XP for your achievement.
The Intermediate R course is taught by DataCamp’s data science instructor Filip Schouwenaars. He has also worked with courses for Python and SQL and is one of the key people behind the development of DataCamp Workspace.
DataCamp Workspace is a unique online integrated development environment (IDE). Here, learners and professionals alike can come together to work on real-life use cases, share their findings, and propose research ideas. You can learn more details on the DataCamp Workspace in our review here.
You can study the first chapter of the Intermediate R course for free. And if you want to keep learning, you can subscribe to one of DataCamp’s learning plans, starting at just $25 a month.
With the Premium plan, you’ll be able to access the whole catalog, including DataCamp R career tracks and courses, as well as numerous projects and even certification programs.
Writing Efficient R Code (Enroll Here)
- Offered by: Colin Gillespie
- Duration: 4 hours
- Price: from $25/month
- Certificate: No
- Level: Intermediate
- Where to apply? HERE
Now that you know the core components of R, it’s time to start thinking about how you’ll write your own code. As a beginner, you might find it easier to strictly follow the rules exactly as you’ve been taught. But that’s not necessarily the most convenient way to code in the real world. So, how about learning some shortcuts and new useful techniques?
Writing Efficient R Code is the third course on the DataCamp R Programming skill track. The title is pretty self-explanatory – the aim is for you to become an efficient programmer that can produce good quality code faster.
This course will help you take your data analysis skills to the next level. While R is the most popular programming language for this purpose, it can be frustratingly slow. So, efficient programming can be pretty vital to keep you from falling behind your schedule.
This four-hour course is also part of the Big Data skill track. As the name implies, it’s focused on managing big data – from its scalability to visualization. Writing Efficient R Code is the first course on this track, so if you plan on working with big data, you can get started here.
Here are the four chapters included in the course:
- The Art of Benchmarking
- Fine Tuning: Efficient Base R
- Diagnosing Problems: Code Profiling
- Turbo Charged Code: Parallel Programming
But don’t let the lengthy names scare you – everything is explained in an easy-to-understand, interactive way, and you’ll get to work on more than 40 exercises that will make everything even more comprehensive.
The Art of Benchmarking will explain why it’s essential for you to track how long it takes for the code you’ve written to run. Spoiler alert: setting a benchmark helps you perceive improvement in the speed of your code.
The Fine Tuning chapter will help you learn to ensure that your base code is fast. You’ll dip your toes in data frames and matrices and see the most common culprits that slow down your code.
Diagnosing Problems will show you what you need to do if you encounter any bottlenecks. You’ll learn about the process of profiling and what strategies to use if you encounter unexpected issues.
Finally, in the Turbo Charged Code chapter, you’ll try out an exciting new strategy – you’ll see how to run parallel codes on multiple cores to significantly improve your code performance. It’s not all about how your write the code – it’s about what hardware you use to run it, too.
The Writing Efficient R Code course is guided by Colin Gillespie, Associate Professor of Statistics at Newcastle University. Given his academic experience, you’ll certainly be in good hands. You can also check out his Defensive R Programming course, which will teach you how to catch bugs and reduce the number of errors in your code.
You can check out the first chapter of the course, The Art of Benchmarking, free of charge today. And, if you want to learn everything, you can sign up for the DataCamp Premium plan for $25/month. It'll grant you access to all courses and tracks mentioned so far, including the Big Data track and the Defensive R Programming course.
Introduction to Writing Functions in R (Enroll Here)
- Offered by: Richie Cotton
- Duration: 4 hours
- Price: from $25/month
- Certificate: No
- Level: Intermediate
- Where to apply? HERE
I briefly mentioned something important in the Intermediate R section: functions are one of the key elements of just about all programming languages, including R. Functions are essentially what makes your code work. They’re also reusable, so it’s more than handy to learn how to write them yourself.
The Introduction to Writing Functions in R course will guide you through the process of writing functions specifically for data analysis. Knowing them will help you be more productive while you work and know what parts of code you can reuse in the future.
This course will give you the foundation to write your own functions. As with all DataCamp R courses, you won’t just be learning the theory. You’ll also have the opportunity to explore real-world data and try your hand at over 50 exercises. The four chapters will take you four hours to complete.
In the Introduction to Writing Functions in R course, you will learn function-based skills like:
- Why it's useful to learn to write your own functions;
- How you can convert scripts into functions;
- How arguments work and how to check them;
- Different types of return values;
- How R can determine which variables exist in the code.
Your final task in this course will be a case study, so you'll be able to test your function writing skills. You will go through different stages of data processing, from preparation to visualization. After running through the task one more time, you'll be able to call yourself a proficient R programmer.
By the end of this course, not only will you know how functions work when you code with R, but you'll also be able to set up your own templates that you'll be able to reuse in the future. You can also use the examples provided in the course or check out some of the suggestions in the DataCamp cheat sheets.
But if you want to keep working on your skills, you can check out DataCamp Projects. They are exercises created by professional programmers to help you understand how to perform data analysis in the real world. According to some of the DataCamp R reviews, they’re a great addition to your learning experience.
The Introduction to Writing Functions in R course is taught by Richie Cotton, DataCamp’s curriculum architect. He’s been working with R for nearly two decades and has even authored some books related to programming. As one of the people involved in the platforms’ architecture, he certainly knows what DataCamp R students might need.
If you want to learn the basics of how to write a function, you can access the first chapter of this DataCamp R course for free. The rest will be available for you with the Premium plan for just $25/month.
This will also unlock new opportunities, like joining projects in the DataCamp Workspace and putting your new function skills to the test with DataCamp Competitions. So, why wait? Enroll in the Introduction to Writing Functions in R course and keep fostering your R skills!
Object-Oriented Programming with S3 and R6 in R (Enroll Here)
- Offered by: Richie Cotton
- Duration: 4 hours
- Price: from $25/month
- Certificate: No
- Level: Intermediate
- Where to apply? HERE
We've gotten to the final step before you can wrap up the DataCamp R Programming skill track. By now, you've probably gotten quite good at writing your own R code, and you've probably even started using some of the strategies to be more efficient. So, let's see how object-oriented programming works in R.
R is a multi-paradigm programming language, meaning that programmers can use it for different programming styles, depending on their preferences and needs. One of such styles is object-oriented programming (OOP) which treats data and methods as objects.
Object-Oriented Programming with S3 and R6 in R is perhaps the most tech-savvy course in the R Programming track. It's been developed to help you maintain the complexity of your code. Here, you'll have the opportunity to work with S3 and R6 systems, which are used for object-oriented programming.
Throughout this four-hour course, you will get some hands-on experience with the S3 and R6 systems. S3 is a tool that you can use to simplify your functions, while R6 can be handy if you're working on specific data analyses or web APIs.
Don't let the complexity scare you off, though. You'll be going through everything step by step. First, you'll be introduced to the concept of object-oriented programming. This will answer the questions like what OOP is or when R programmers may need it. You'll also learn what systems are used for object-oriented programming.
Then, you'll get to know S3. It's an object-oriented system that you'll use when you're working with functions. You'll learn about generic functions and create S3 methods.
The following three chapters will cover R6. First, you'll see the basics of using R6. You'll get to create R6 objects. This is an exercise-heavy chapter, so you'll get to learn as you do. Then, you'll learn about inheritance and how to work with parent and child classes in your code.
The final chapter of this course will teach you more advanced methods of working with R6. You will see how references behave and how you can copy them, find out what shared fields are, and learn to clone objects.
The instructor of the Object-Oriented Programming course is Richie Cotton, who you're already familiar with from the Writing Functions in R course. In this course, he'll help you easily understand more complex concepts and systems that you may not have worked with before.
Now that you're practically done with the R Programming skill track, you must be itching for a good challenge. Well, you don't have to wander far to find one – DataCamp has more than one great option for you to test out your skills and keep learning, even when the course is done.
You might already be familiar with DataCamp Projects. They're additional tasks offered to DataCamp learners to help reinforce their programming skills. DataCamp Projects are developed by expert programmers and data scientists. You'll be able to take real-life data and complete various challenges to gain knowledge and experience.
But if you're looking for something more challenging or have already completed every R-related project, why not try your hand at DataCamp Competitions? It's one of the newest perks offered to DataCamp learners that will enhance their experience.
You can join the data science challenges, submit your solutions, and see how good your R programming skills are. While some competitions will award you skills you won't forget, in others, you may win monetary prizes and other goodies.
You can start taking the first chapter of the Object-Oriented Programming with S3 and R6 in R course for free. But if you're looking to finish the entire DataCamp R Programming journey, you can sign up for just $25/month. With the Premium plan, you'll be able to pick from more than 350 courses, find your career track, and learn as much as you want.
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Conclusions
Taking the first step can be the hardest decision you make – where do you start? Which direction should you take? With DataCamp, you don’t need to worry – the jouRney is set ahead of you, and all you need to do is join the DataCamp R Programming skill track.
Don’t just take my word for it, though. DataCamp is one of the top-rated learning platforms in the world, and the DataCamp R reviews agree that the courses are both great for beginners and fun to follow along.
So, if you’re looking for a place to start learning R without getting bored, the DataCamp R courses might be a great choice for you.
And if you ever decide to venture even deeper into data science, you can put your DataCamp Premium membership to good use. From career tracks and programming courses to real-life projects in the workspace and even competitions with impressive rewards – why not stick around? You can even find discounts and special offers here.
Here’s my tip – add another language to your growing skill set, check out our look into the best DataCamp Python courses here, and keep learning.
Scientific References
1. Vailshery, L. "Most used programming languages among developers worldwide, as of 2021"
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