R Programming Exercises : Matrices (with answer code)

Programming Exercises for R programming. Basics of R. Chapter : Matrices
Answers included with compiled R codes.
Tricky exercises for the practice of matrices using R code.

https://drive.google.com/open?id=0BzC2zFSTPOH3N2tpdnQ3akVlVWc

R Programming Exercises : Vectors (with answer code)

Programming Exercises for R programming. Basics of R. Chapter : Vectors
Answers included with compiled R codes.
These are the simple practice questions for Vector questions in R programming.
https://drive.google.com/open?id=0BzC2zFSTPOH3R3ZKRElUS2JNaGs

Some interesting R programming codes

These are the some of the interesting R codes. 
Very useful for beginners

https://drive.google.com/open?id=0BzC2zFSTPOH3OHFLd3p0XzVudU0

The importance of R for Data Science

R is very important in data science because of its versatility in the field of statistics. R is usually used in the field of data science when the task requires special analysis of data for standalone or distributed computing.

R is also perfect for exploration. It can be used in any kind of analysis work, as it has many tools and is also very extensible. Additionally, it is a perfect fit for big data solutions.

Following are some of the highlights which show why R is important for data science:
Data analysis software: R is s data analysis software. It is used by data scientists for statistical analysis, predictive modeling and visualization.
Statistical analysis environment: R provides a complete environment for statistical analysis. It is easy to implement statistical methods in R. Most of the new research in statistical analysis and modeling is done using R. So, the new techniques are first available only in R.
Open source: R is open source technology, so it is very easy to integrate with other applications.
Community support: R has the community support of leading statisticians, data scientists from different parts of the world and is growing rapidly.

So, most of the development of R language is done by keeping data science and statistics in mind. As a result, R is become the default choice for data science applications and data science professionals.

Why you should learn Python and Hadoop ?

With big data analytics continuing to achieve prominence at a number of software services companies, its popularity is growing to unprecedented levels. As big data analytics happens to offer many perks as well as great packages, it makes for a great choice for anyone looking to pursue a fulfilling career. Armed with certifications from various professional training institutes like GreyAtom, Aegis, Imarticus Learning, as a candidate you have millions of opportunities opened up for you. So if you are looking for a serious career change, or have plans of starting off in the data science industry, you would have a few questions. One of them being which data analytics tool should you master? The answer to this question would most certainly be either Hadoop or Python or both.

Python

Let’s begin with Python, due to its great similarities with tools like Java, C or Perl, the basics here are the easiest to master for the novices. As this tool happens to be very beginner friendly, a freshly graduate programmer would find it be a perfect fit. With having to write less code and other features like code readability, simple syntax and easy implementation, it happens to be one tool that every data analytics aspirant must study.For any Python programmer, the most difficult task is finding out bugs and squashing them, but in Python its unique design lends itself really well to all of its users. Writing less code, basically means that the programmers would find debugging easier and will also be prone to fewer issues as compared to other programming environments.In addition to all the above winsome attributes, Python also happens to be an object oriented language. This would make it easier for the user to migrate to any other object oriented language, just by learning the syntax of the new language. But one of the most important reasons why you should learn Python is, that it can power Google’s search engine, YouTube, Dropbox, Mozilla, NASA and IBM too.

Hadoop

Moving on to Hadoop, this is an open sourced software framework, which is very easily able to store and process great amounts of data. Many professionals have been blown away by its sheerhorse power. It has the ability to make a huge difference to many organizations by assisting them in their marketing needs.It so happens that Hadoop and NoSQL are believed to be the fastest growing technological networks in the market of Data Science. There have been reports which state that Hadoop will possibly grow in the Big Data Market and reach up to $13.9 billion by the year 2017.As Hadoop has quite a lot of implementations, professionals who have expertise in this Hadoop programming language have a wide range of career roles to choose from. All one needs to have,is the deep rooted understanding of how the framework of Hadoop works. As it is one of the most sought after skills, it also pays really well Thus, here we have the most touted reasons, as to why one must study Hadoop and Python.