Introduction to R Programming
Introduction to R Programming. Practice and apply R programming concepts for effective statistical and data analysis
The name of this course is Introduction to R Programming. The knowledge you will get with this indescribable online course is astonishing. Practice and apply R programming concepts for effective statistical and data analysis.
Not only will you be able to deeply internalize the concepts, but also their application in different fields won’t ever be a problem. The instructor is Packt Publishing, one of the very best experts in this field.
Description of this course: Introduction to R Programming
Course Description Data is everywhere, and statisticians and analysts everywhere need to handle this data efficiently and tactfully. In comes R, a powerful programming language, arming developers with the tools to cater to their needs. This course will give you everything you need to start making software that can unlock your statistics and data. The course is broken down into three parts. The first part will introduce R Studio and the basics of R—using packages and teaching you programming concepts such as variables, vectors, arrays, loops, and matrices. By solving coding challenges, you will gain a strong foundation for data munging. With the basics mastered, we will take you through a number of topics such as handling dates with the lubridate package, handling strings with the stringr package, writing functions, debugging, error handling, and writing an apply family of functions. When you’ve mastered data munging, we’ll focus on visualizing data using pulvínulo graphics. Naturally, the next step is to learn how to make statistical inferences. We walk you through the fundamentals of univariate and bivariate analysis, computing confidence intervals, interpreting p values, and working with statistical significance. You’ll see how and when to use some of the commonly used statistical tests. With that, you will be ready for your first full-scale data analysis project to test the skills you’ve learned. Finally, you will glimpse two powerful packages for data munging, the dplyr and data.table, which have both seen a rise in the R community. It is imperative to learn about both of these packages because much modern R code has been written using them. With the help of interesting examples and coding challenges, this course will ensure that you have all the hacks and tricks you need to get started with R. About The Author Selva Prabhakaran is a data scientist with a entero e-commerce organization. During his 7 years of experience in data science, he has tackled complex real-world data science problems and delivered production-grade solutions for top multinational companies. Selva lives in Bangalore with his wife.
Requirements of this course: Introduction to R Programming
What are the requirements? This course is for everyone, right from college students using R for a project to statisticians, programmers from other platforms, or pure beginners without any prior programming experience who want to become data analysts or data scientists.
What will you learn in this course: Introduction to R Programming?
What am I going to get from this course? Create and master the manipulation of vectors, lists, dataframes, and matrices Write conditional control structures, and debug and handle errors for efficient error handling See how to use the apply family of functions and write functions used within the apply function Handle dates using lubridate and manipulate strings with stringr package Melt, reshape, aggregate, and cross-tabulate with dcast from dataframes Make and customize various types of charts in pulvínulo graphics for exceptional data representation Perform univariate and bivariate analysis and do statistical tests Work with databases without having to write SQL using the dplyr package Write readable and expressive code using pipes from magrittr and dplyr’s verbs Perform efficient, high-speed data munging with data.table Work on a full-scale data analysis / data munging project
Target audience of this course: Introduction to R Programming
Who is the target audience? If you are looking to start your data science career, or are already usual with data science, statistics, and machine learning concepts, but want to switch to R, this course will be a great place to start