R Language in Data Science

R Language
R Language in Data Science
R Programming
R Programming in Data Science
R Language for Statistical analysis

Hello, welcome to this Introduction to R course. In this course, we will help you lay a solid foundation for using the R programming language for data science. You may be a data scientist looking for insights from your data, a researcher looking to quickly analyze your experimental data and validate your scientific hypothesis, a software developer looking to step up to a new career as data scientist, or a new graduate seeking to establish a solid skillset to score a job in data science. Regardless of your goals, you may wonder which programming language to choose. Is R the right choice? Yes, it is. R is one of the most widely used languages for data analytics and data science, especially for statistical computing. So, what makes R so good? First, R is an open-source language, which means you can review the source code for free and even modify it. Being open-source, you can leverage and integrate cutting-edge research into your analytics, such as the latest AI algorithms. Second, R has rich data science libraries that include everything you need to do data processing, data visualization, and modelling to facilitate your own research and development. Third, R is simple and easy to understand. Its simple syntax allows you to learn it very quickly. Finally, R has an extensive and rich community of support, so you can very easily find answers to your questions online. R has been a very popular language since 2014. According to the TIOBE index, which is an indicator of the popularity of programming languages, R ranked 8th in 2020. This is a very high rank out of the hundreds of programming languages available today. So, get ready to learn the powerful and popular R language for your data science endeavors! To learn effectively and efficiently from this course, view every video, check your learning by taking each quiz, connect to your peers in the discussion forums, and consolidate your R coding skills by completing the hands-on labs and the final project. Now, equip yourself with new R skills and then take the next step along an exciting journey that leads to the world of data. Good luck!