R is a popular choice of tool for data science professionals, offering a large variety of libraries pertaining to each and every task in data science. With practical examples based on various real-world domains and use-cases where R and its libraries can be used, this course will be your companion for implementing those tasks using the free, open source libraries provided by R.
This comprehensive 2-in-1 course equips you with all the essential skills required to perform data science tasks with ease using practical, real-world scenarios. It follows a step-by-step approach to teach you the fundamental concepts of R programming and usage of its libraries such as, setup, working with complex data, performing data analysis, data mining, and data visualization with ggplot2, Plotly, Leaflet, GoogleVis, Motion Chart, and Joy of Stats.
This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Speaking 'R' - The Language of Data Science, begins with an introduction to R and setting up the development platform. You will then be introduced commands in R, which are very useful and not as common in traditional languages since manipulating data is more important in R. You will also look at an example of Titanic dataset, which is the kind of thing you'll come across in R, a multidimensional collection of variables of different types. Using the tools that we cover we can form a picture, a story behind the data. Next, you will learn how to clean up the data. Finally, you will learn some basic statistics with R using special features for data visualization.
In the second course, Heavy-Lifting Using R Libraries, you will begin by looking at high-performance computing in the classic, computationally intensive scenario: finding prime numbers. You will then learn how to use R, before moving on to using C++, which is far faster. Next, you will use the power of parallel, though that varies from problem to problem since some are more suitable for parallelization. Finally, you will look at some powerful options available in R where you don't just produce a static result but instead respond to user selections.
By the end of this course, you will be able to confidently use the R programming language for performing data mining, data analysis, and data visualization.
Meet Your Expert(s):
We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:
Dr. Samik Sen is a Theoretical Physicist and loves hard problems to think about. After his Phd, which was about developing computational methods to solve problems for which no solutions existed, he began thinking about how to tackle the maths problem while lecturing. He developed algorithms to generate problem sets and solutions, and learned how to create video lessons. He has developed a large Facebook community teaching school maths around Ireland, with associated e-learning products and YouTube channel. Samik is currently fascinated by machine and deep Learning.He has developed a machine learning system which is performing better than he can himself which was the hope.