Learn R Programming | R Online Course | Udacity (2024)

FAQs

What is the best way to learn R programming? ›

R is considered one of the more difficult programming languages to learn due to how different its syntax is from other languages like Python and its extensive set of commands. It takes most learners without prior coding experience roughly four to six weeks to learn R.

Can I learn R on my own? Of course, you can. In fact,many working programmers don't have a computer science degree and have learned how to program outside of college. While many programming jobs do require a degree, it does not have to be in computer science.

Is Python or R easier? Python is much more straightforward, using syntax closer to written English to execute commands. However, R makes it easier to visualize and manipulate data if you have other languages under your belt. It's statistics-based, so the syntax here is more straightforward for analysis.

R has a reputation of being hard to learn. Some of that is due to the fact that it is radically different from other analytics software. Some is an unavoidable byproduct of its extreme power and flexibility. And, as with any software, some is due to design decisions that, in hindsight, could have been better.

It's a really comprehensive course and teaches you the basics of using R from no knowledge of programming beforehand. When you get stuck, the tips and solution may be able to help you understand what went wrong.

R is a great language for programming beginners to learn, and you don't need any prior experience with code to pick it up. Nowadays, R is easier to learn than ever thanks to the tidyverse collection of packages.

Both languages are well suited for any data science tasks you may think of. The Python vs R debate may suggest that you have to choose either Python or R. While this may be true for newcomers to the discipline, in the long run, you'll likely need to learn both.

While there are many languages and disciplines to choose from, some of the most popular are R and Python. It's totally fine to learn both at the same time! Generally speaking, Python is more versatile: it was developed as a general-purpose programming language and has evolved to be great for data science.

R's popularity can be attributed in part to its extensive selection of visualization libraries. Consequently, there is currently a high demand for professionals who specialize in Data Visualization using R programming.

Can I get a job with only R programming? ›

Although it's essential to look at some different programming careers and the languages they use regularly, R will open opportunities for you to pursue a career in several data analytics and statistics-based positions, such as data scientist, data analyst, data architect, statistician, or data engineer.

How long does it take to learn R? If you have no prior coding knowledge, it will take 4-6 weeks to wrap your head around R's foreign syntax. Unlike other coding languages like Python, R's syntax is nothing like English and takes getting used to.

R and SQL are both languages that are commonly used for data analysis. The main difference between the two is that R is a programming language that is specifically designed for statistical computing and data analysis, while SQL is a language that is used for managing and querying data stored in relational databases.

R can't be used in production code because of its focus on research, while Python, a general-purpose language, can be used both for prototyping and as a product itself. Python also runs faster than R, despite its GIL problems.

While python codes are easy to understand and capable to do more data science tasks in general. On the other hand, R codes are in the basic academic language, easy to learn, and the best effective tool for Data Analytics tool in visualization.

The course from Great Learning Academy, Introduction to R, is free for anyone interested in learning new skills. Professionals who want to upskill by studying R programming can start this course.

Both languages are well suited for any data science tasks you may think of. The Python vs R debate may suggest that you have to choose either Python or R. While this may be true for newcomers to the discipline, in the long run, you'll likely need to learn both.

Python has more features and more support, making it more likely you'll find the tools you need to get projects done. R is less popular, but better for data science tasks like analyzing data and creating visual data.