R is a system for statistical computation and graphics. It provides, among other things, a programming language, high level graphics, interfaces to other languages and debugging facilities. This manual details and defines the R language.It is possible to get quite far using R interactively, executing simple expressions from the command line. Some users may never need to go beyond that level, others will want to write their own functions either in an ad hoc fashion to systematize repetitive work or with the perspective of writing add-on packages for new functionality. Start learning with us ACTE R Programming Classroom & Online Training Course.
R Programming is very useful for career.Careers in R programming are associated with the data science and business analytics profession. ... R programmers are a good fit for the research-oriented industry for statistical model implementation for data analysis. professionals want to upgrade their career in data science R programming is a preferred choice.
R Programming, have great scope, Scope is high Basically, R is now considered as the most popular analytic tool.R Careers offers bright jobs for any data scientist he may be any fresher or experienced. Organizations expect many of the new hires with knowledge of R and they want them to be familiar with the R tool.
Even as a fresher, you can get a job in R Programming domain. R is the name of a popular programming language that has become the tool of choice for data scientists and statisticians around the world. Companies are using analytics to predict things like pricing of their products, how much to spend on ads, whether a drug will turn out to be successful or not etc. and R is helping them analyse historical data to make these predictions.
The business analytics field has been dominated by paid tools such as SAS, Statistica and SPSS (IBM). Even though some of these tools can be very expensive (with software licenses running into millions of dollars), the value coming out of their application is far more and hence companies did not mind spending so much.
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for R Programming. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
Coin package in R provides various options for re-randomization and permutations based on statistical tests. When test assumptions cannot be met then this package serves as the best alternative to classical methods as it does not assume random sampling from well-defined populations.
- Knowledge of statistics theory in mathematics.
- You should have solid understanding of statistics in mathematics.
- Understanding of various type of graphs for data representation.
- Prior knowledge of any programming.
Learn R. Can someone with no programming knowledge learn “R”? The answer is yes! ... Despite not having any previous programming experience , I analyzed my first data set of more than 20,000 data points in only a couple of months.
Our course ware is designed to give a hands-on approach to the students in R Programming. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
Yes Definitely! From my point of view learning, R language has a worth to learn. R is the best programming language to perform analytical operation. The number of applications such as healthcare, finance, media use R programming to analyze their data.
Advanced R Programming takes around 1 month to master to a level so that you can start writing analytics functions.
If you have experience in any programming language, it takes 7 days to learn R programming spending at least 3 hours a day. If you are a beginner, it takes 3 weeks to learn R programming. In the second week, learn concepts like how to create, append, subset datasets, lists, join.
- Backed by a Huge, Active Community.
- Comprehensive Library Support.
- Cross-Platform Compatibility.
- Data Visualization at its Best.
- Develop Interactive, Powerful Web Apps With Shiny.
- Go-to Option for Statistical Analysis and Data Science.
- High Market Demand With High-Paying Roles.
- Major Companies Trust R.
Why Learn R Programming?
There are various reasons to learn R, we have listed the major ones that will surely answer your question to why learn R.
1. Why R is important for Data Science?
R plays a very important role in Data Science, you will be benefited with following operations in R.
- You can run your code without any compiler– R is an interpreted language. Hence we can run code without any compiler. R interprets the code and makes the development of code easier.
- Many calculations done with vectors – R is a vector language, so anyone can add functions to a single Vector without putting in a loop. Hence, R is powerful and faster than other languages.
- Statistical Language – R used in biology, genetics as well as in statistics. R is a turning complete language where any type of task can perform.
2. Why R is Good for Business?
R will just not help you in the technical fields, it will also be a great help in your business.
- Here, the major reason is that R is open-source, therefore it can be modified and redistributed as per the user’s need. It is great for visualization and has far more capabilities as compared to other tools.
- For data-driven businesses, lack of Data Scientists is a huge concern. Companies are using R programming as their core platform and are recruiting trained R programmers.
3. R is a gateway to Lucrative Career
R language is used extensively in Data Science. This field offers some of the highest-paying jobs in the world today. Data Scientists who are proficient in R make more than $117,000 (Rs 80,56,093) on an average per year. If you want to enter the field of Data Science and earn a lucrative salary, then you must definitely learn R.
4. Open-source
R is an open-source language. It is maintained by a community of active users and you can avail R for free. You can modify various functions in R and make your own packages. Since R is issued under the General Public Licence (GNU), there are no restrictions on its usage.
5. Popularity
R has become one of the most popular programming languages in the industries. Conventionally, R was mostly used in academia but with the emergence of Data Science, the need for R in the industries became evident. R is used at Facebook for social network analysis. It is being used at Twitter for semantic analysis as well as visualizations.
6. Robust Visualization Library
R comprises of libraries like ggplot2, plotly that offer aesthetic graphical plots to its users. R is most widely recognized for its stunning visualizations which gives it an edge over other Data Science programming languages.
7. With R, you can develop amazing Web-Apps
R provides you with the ability to build aesthetic web-applications. Using the R Shiny package, you can develop interactive dashboards straight from the console of your R IDE. Using this, you can embed your visualizations and enhance the storytelling of your data analysis through aesthetic visualizations.
8. R enjoys a vast Community Support
R Programming is supported by a vast community that maintains and updates R. If you face any trouble with the code in R, you can avail the support of the community on places like Stack Overflow (of course you can also ask us any queries in the comment section below, DataFlair is always there for you!). There are several communities around the world that organize bootcamps and R meetups.
9. A go-to language for Statistics and Data Science
R is the standard language for Statistics and Data Science. R was developed for statistics, by statisticians. It has been in use even before the word “Data Science” was coined. Statisticians and Data Scientists are most familiar with R than any other programming language. R facilitates various statistical operations through its thousands of packages.
