R for Data Science Data science Data science is a booming field in today’s world. Since Artificial Intelligence is the main focus of today’s technology, data science automatically comes in the picture. Data science and machine learning can be considered as the base of Artificial Intelligence. There are many programming languages involved in data science, one of them being R. R is a programming language which is mostly meant for data science because of its explicit features. It is used by many companies like Facebook, Airbnb, Uber, etc. R is explicitly used for data science, analysis and for computing statistics. The reason for R being a popular programming language for data scientists is because it is open and free to use. It also runs on all platforms and its characteristics are meant for research and statistical analysis of data. R is a language which also includes machine learning algorithms along with statistical characteristics which makes it perfect for data science. Statistical interference, Machine Learning Algorithm and Data science are the main purpose for R as a programming language. R is a programming language used by data scientists worldwide, but there are some common steps which they follow while analyzing data using R. They are total in five and precise. They are as follows: ● The first step is programming where R is used as a programming tool to access data. ● The second step is transforming the accessed data and distributing it to various libraries which are exclusively designed for the process of data science. ● The third step is to analyze, discover and research the given data and build a hypothesis on them. ● The fourth step is modelling your data by using specific tools provided by R. ● The fifth and the final step is to communicate your research and analysis in the form of codes, graphs, algorithms which are used by various apps and more. When it comes to data science, your research and analytical skills are considered more important than your knowing any programming language. Knowing a programming language is just a bonus and helps youdata science

communicate your analysis in a better way. In data science, R and Python are the main programming languages used. It just increases your possibilities of getting a job in the field of data science. Learning R helps you with better statistical analysis and setting better machine learning algorithms when you are analyzing large amounts of data almost every day as a data scientist. R was considered to be a difficult programming language to learn, but as time passed it has become easier to learn R. It had a very intricate structure which made it confusing. The biggest advantage of R is that it is available on various platforms. It is possible to call different languages like Python, Java, C++, etc. in R. You can create the best machine learning algorithms on R which are more effective than any other programming language. Since data science is very much in demand, the competition for jobs is increasing day by day. Therefore, learning R is always beneficial from a career aspect. Resource Box: Data scienceData science is a highly demanding field and requires trained professionals for this job. Therefore, learning various programming languages is always beneficial. There are many places and online websites which offer to teach a basic crash course about R. They are easily available and easily accessible to the common man.