Are you looking forward to enter into the data science world? Or are you a data scientist and want to explore R to make your job easier? If yes, this course is ideal for you.
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 the course is to help you learn programming in R as well as to perform data analysis, data visualization, and data manipulation using R.
What is included?
This course is meticulously designed and developed in order to empower you with all the right and relevant information on R. However, I want to highlight that the road ahead may be bumpy on occasions, and some topics may be more challenging than others, but I hope that you will embrace this opportunity and focus on the reward. Remember that throughout this course, we will add many powerful techniques to your arsenal that will help us solve the problems.
Let’s take a look at the learning journey. 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 the course, you should be able to put your learnings into practical use immediately.
Why should I choose this course?
Packt courses are very carefully designed to make sure that they're delivering the best learning experience possible. This course is a blend of sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. This helps you learn a range of topics at your own speed and also move towards your goal of learning the technology. We have prepared this course using extensive research and curation skills. Each section adds to the skills learned and helps you to gain knowledge in R. We hope that you enjoy this and any other courses you might purchase from Packt.
This course is an amalgamation of sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. We have combined the best of the following Packt products:
Meet your expert instructors:
For this course, we have combined the best works of these extremely esteemed authors:
Kun Ren has used R for nearly 4 years in quantitative trading, along with C++ and C#. He has worked very intensively on useful R packages that the community does not offer yet. He is also a frequent speaker at R conferences in China and has given multiple talks. Additionally, he has substantially contributed to various projects on GitHub.
Selva Prabhakaran is a data scientist with a large e-commerce organization. In 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.
To run and write code in R, we first need to focus on how to get and install the IDE:
We have installed R and RStudio. Now let's check out how to install the packages:
In this video, we will see how to work with vectors in R.
The aim of this video is to show how to work with random numbers and do rounding and binning:
Taking vectors a step ahead, let's see how we can handle missing values:
We now know a lot about how vectors work, but how do we get specific items from a vector based on any condition? In this video, we'll learn how to write conditions, how to write complex conditions, and how to use the
which()operator to get the required items:
The aim of this video is to introduce a new data structure list and how to work with it:
The aim of this video is to understand how to perform set operations in R:
In this video, you will learn to perform sampling and sorting operations:
Checking conditions is often a requirement for a programmer to write maintainable code. in this video, let's understand how to check conditions in R:
In this video, you will learn how to handle date variables in R with introduction to
lubridate package and performing date operations:
In this video, you will perform string operations in R with an introduction to the
Functions help you to avoid repetitions. In this video, you will learn the best practices for writing functions in R:
In this video, you will learn how to debug and handle errors:
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