Duration: 10 hours

R is one of the leading languages which is preferred in the data science world. It is an open source programming language and software environment for statistical computing and graphics and is highly extensible. This programming tool is used for performing data import and cleaning, exploration and visualization, statistics and analysis. It is also useful for trading simulations, production, and trading applications.

The aim of this course is to equip you with the concepts and practical applications that will allow you to use R for performing data import and cleaning, exploration and visualization, statistics and analysis.

The course begins with installation of R, RStudio and all the necessary R packages. Then, you’ll work with some built-in functions in R. Also, you’ll work with data and strings. Next, you’ll learn core programming, object-oriented programming, and metaprogramming concepts and best practices in it. Moving ahead, you’ll learn to create, design, and customize plots with base graphics. Also, you’ll understand and perform Univariate analysis. Further, you’ll gain knowledge on Chi-sq test, ANOVA, and statistical tests for analyzing numeric and categorical data. Also, you’ll perform tasks on these along with a practical example of full scale data analysis project. Finally, you’ll learn about the two most popular data manipulation packages, dplyr and data.table which are essential while working with large data and also Pipe operators which will massively increase the code readability.

By the end of this course, you’ll know how to write code in R and perform data analysis, data manipulation, and visualizations more efficiently and effectively by creating different types of charts and graphs.

What am I going to get from this course?

• Explore R language from basic fundamentals to advanced topics
• Create and master the manipulation of vectors, lists, dataframes, and matrices
• Deep understanding of core programming, metaprogramming, and object-oriented programming concepts and best practices in it
• Make and customize various types of charts in base graphics for exceptional data representation
• Perform univariate analysis and do statistical tests
• Work on a full-scale data analysis project
• Write readable and expressive code using pipes from magrittr and dplyr’s verbs

Style and Approach

Starting from the ground up and moving towards intermediate level, this course will help you gain a wholesome knowledge on R programming concepts and data science in a step-by-step approach with examples and solving challenges.

This course is a blend of text, videos, code examples, and assessments, all packaged up keeping your journey in mind. The curator of this course has combined some of the best that Packt has to offer in one complete package. It includes content from the following Packt products:

• Learning R Programming by Kun Ren
• Introduction to R Programming by Selva Prabhakaran

Note: This interactive EPUB adheres to the latest specification, and requires that your reader supports video and interactive content. We recommend using Readium with the latest stable version of Google Chrome, or iBooks for OS X.