R: Programming and Data Science | Data Science Online Course by Udemy

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Become proficient in statistical and data analysis with R programming concepts

An excellent training about Data Science

R: Programming and Data Science

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. Lets take a look at the learning journey. The course begins with installation of R, RStudio and all the necessary R packages. Then, youll work with some built-in functions in R. Also, youll work with data and strings. Next, youll learn core programming, object-oriented programming, and metaprogramming concepts and best practices in it. Moving ahead, youll learn to create, design, and customize plots with base graphics. Also, youll understand and perform Univariate analysis. Further, youll gain knowledge on Chi-sq test, ANOVA, and statistical tests for analyzing numeric and categorical data. Also, youll perform tasks on these along with a practical example of full scale data analysis project. Finally, youll 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 anamalgamationof 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: Learning R Programming by Kun Ren Introduction to R Programming by Selva Prabhakaran Meet yourexpert instructors: For this course, we have combined the best works of these extremely esteemed authors: Kun Renhas 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 Prabhakaranis 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.

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