Begin learning software, finance, data, design and business skills - anytime, anywhere - with our video tutorials.
This is a online course is to gain comprehensive Practical understanding of R Programming. The aim is to learn essential concepts in R Programming right from scratch. The tutorials will help you learn about Introduction to R Programming, Datatypes and Basic Operations, Reading Data, Understanding Functions, Scoping Rules, Looping, Simulation & Plotting, Date ,Time & RegEx and Classes & Methods.
R is a powerful language and environment that is used for statistical computing and graphics. Very similar to the S language and environment that was developed at Bell Laboratories by John Chambers and colleagues, while the R programme was a part of the GNU project. R can be considered as a different implementation of S and there are some important differences while so much of their code is similar for both S and R.
R provides a lot of variety for statistical including linear and non linear modeling, classical statical tests among others as well as for graphical technique which is quite extensible. The S language is, therefore, a great choice for research in statistical method and R provides an Open source to match the requirements.
One of the biggest strengths of R is that it is easy to integrate it with publication quality plots including symbols and formulas related to mathematical equations. So while great care has been taken to ensure default choices in minor design changes, the user is more often than not in full control of the software. In addition, R is available as a free software under the terms and conditions of Free Software Foundation’s GNU General Public License. It is capable of being compiled and run on a number of platforms including UNIX platforms, MacOS and Windows.
An integrated suite for software facilities that are used for data manipulation, calculation, and graphical display, it has the following features:
In short, R is a programming language and software environment that is used for statistical computing and graphics. The R language is further mostly used by statisticians and data miners so that they can develop new and innovative statistical software and data analysis methods. Polls, surveys of data miner and studies have effectively proved that the popularity of R software has increased substantially in the recent years.
Some of the benefits of R programming include the following:
Many of us have heard it that statistics is one the next sexy jobs that are coming up in the career opportunities (this fact is vouched by even Hal Varian). Almost five years Tim O’Reilly said that data is the next big thing to happen in the world. But what exactly is data and why is it so important? And why is there so much importance being given to statistics and data in the world today?
The web is full of apps that are driven by data. All the e-commerce apps and websites are based on data in the complete sense. There is a database behind a web front end and middleware that talks to a number of other databases and data services. But the mere use of data is not what comprises of data science. A data application gets its value from data and in the process creates value for itself. This means that data science enables the creation of products that are based on data.
One of the earliest data products that were available on the internet was the CDDB database which was when the developers of this product realised that CD had a unique signature for all the tracks that were recorded on the CD. This is what inspired the Gracenote to build a database of track lengths and with it added the metadata of the album. A good example of this is when you make use of iTunes to rip a CD, then this is an example of the kind of the database. So before iTunes does anything, it reads the length of every tack and then sends to the CDDB software. After this, it gets back to the track titles. In case you have a CD that is not created by you then you can make an entry for an unknown album. While this might sound relatively simple, it was a revolutionary step in the field of data management. This is because the CDDB software was viewing music as data and not as an audio source and thereby creating massive value for it. So while the CDDB software had nothing to do with music, it was revolutionising the industry, just by viewing the audio issue within the industry as an issue that deals with data.
Google has always been an expert at creating data products. Some instances where they have done this include the following:
This is not to say that Google is the only company that is making use of data in an effective fashion. Facebook and LinkedIn are other big social media giants that make use of data to suggest patterns of friendship relationships. or people a user might know, with amazing accuracy. In a similar manner, Amazon saves the search, correlates the searched item and comes up with an appropriate recommendation that in turn help to drive the retail business of the brand. They have come to understand that a book is not just a book, a gadget is not just a gadget and a customer is much more than a customer because they leave behind a trail of data that can be mimed and put to use in an effective fashion. The thread that ties most of these applications together is that through these above sources value can be added to the data collected. So whether data is collected in terms of voice searches or product reviews, they all contribute in adding value and this is, in reality, the essence of data science.
A basic training in R programming is a really good idea because it will help you learn the fundamentals of R that are necessary for data analysis and interpretation. Here are some skills that individuals will need to possess before they enroll in this course:
R Programming for Data Science ideal target audience for this course would include individuals who are trying to get into analytics domains. Graduates who are trying to discover a new career field and are passionate about working in an exciting industry is also perfect for this course. In addition, anyone who wants to learn about R programming would be an effective target audience for this course as well.
Definitely not. In fact, most of the skills needed for students who want to learn about data science is pretty easy especially if you are passionate about the field. Many individuals who have a basic understanding of statistical analysis and data interpretation can successfully complete this course. In fact, after learning about this software, they can effectively enhance their resume as they will have an extra competitive edge over other applicants and people who are in the same field.
There are many institutes and organisations that offer this kind of training for individuals who are interested. In fact, learning about data science using R programming is one way in which statistical reasoning students can stand out in the crowd. At EDUCBA, we bring together the best resources and techniques to help our students gain an intricate and detailed understanding of the R software and the manner in which data impacts organisations/companies. After this course, individuals will be able to help brand managers and website owners to use data in a manner that will empower and strengthen their brand image, not just locally but globally as well.
The R Programming for Data Science course was very
effective and really helped to deepen my understanding about the entire industry. It also helped me to gain rare insight into how brands can make use of data so as evolve and grow in a strategic manner. The examples provided by the teachers made it very simple for us to understand all the concepts.
Hi, my names is Richard Mark. I enrolled for this course out of curiosity and it was a great opportunity for me to learn about data science and its related fields in an effective fashion. I fully recommend this R Programming for Data Science course for people who wish to be experts in the field of data analysis and research. A very easy course, it is very valuable to enrich your career in a profitable manner.
Everyone knows that data is what is driving the world today. And without a proper understanding of how to create value from the volumes of data lying around in every office, no brand can maximise its potential and reach. This has effectively created the need for individuals who can not just understand data bit help brands to discover value from them. That is why there are multiple benefits for individuals to invest their time and resources in learning about data in an effective manner. When brand managers can effectively understand data, they can have a direct impact on various aspects of their brand including customers, target audience, goal creation, and management of resources.
Understanding the world of data science can, therefore, help
you to broaden your understanding of the field on one hand and improve your resume value on the other hand. This can make you a valuable addition to the company in an effective fashion.
|Where do our learners come from?|
|Professionals from around the world have benefited from eduCBA’s Learn R Programming for Data Science Courses. Some of the top places that our learners come from include New York, Dubai, San Francisco, Bay Area, New Jersey, Houston, Seattle, Toronto, London, Berlin, UAE, Chicago, UK, Hong Kong, Singapore, Australia, New Zealand, India, Bangalore, New Delhi, Mumbai, Pune, Kolkata, Hyderabad and Gurgaon among many.|