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Complete R course for Data Science with Tidyverse


Complete R course for Data Science with Tidyverse


Complete R course for Data Science with Tidyverse Learn to program with R, R Studio and Tidyverse: Data Analytics, Data Science, Statistical Analysis, ggplot2 and much more

What you'll learn

  • Learn to program with R from scratch to a high level
  • Learn the fundamental principles of functional programming, such as variables and functions
  • Learn data types such as integers, Booleans, doubles, strings, and structures such as vectors, data frames, and tibbles.
  • Carry out complete and functional graphical representations thanks to ggplot2 from tidyverse
  • Have a good intuition of most of the techniques that apply to the world of machine learning and data science
  • Give added value to your own company or business
  • Do very powerful and accurate analysis with free R and R Studio packages
  • Be a Jedi Master of Machine Learning and Data Science with R Studio and tidyverse


Data Science Fundamentals with R Studio and Tidyverse, with real exercises and examples of all kinds. The indispensable prerequisite to then continue with the complete Machine Learning Course with R Studio by Professor Juan Gabriel Gomila

Welcome to this magnificent and complete R Studio and Tidyverse course where the objective is to train you to be a good data science with the essential fundamentals of using the R and R studio statistical software packages and that you can carry out complete data analysis and from scratch without previous experience. Here you will have everything you need to later continue with courses such as those of Machine Learning with R or with Python that I have published right here on Udemy with all the essential knowledge well established and complete. Based on the free Tidyverse manual, R for Data Science by Garrett Grolemund and Hadley Wickham, and adapted with fun, real-life case examples, you have everything you need to learn how to be a true data analyst in a fun way.

In particular, I have many things to teach you as the work of the data scientist is very varied and fun.

  • You will use R from scratch to become a professional, placing a lot of emphasis on the different parts that compose it, on the basic syntax of creating scripts, the generation and export of graphics, installation of various libraries and much more.
  • You will learn to use ggplot2, a very complete library for graphical representations based on the use of layers of information to make the graph more and more complete and advanced with which to transmit everything you have been learning.
  • You will organize and manipulate data with dplyr, the library for working with data as if it were a database with which you will select, order and create new variables for later analysis and graphic representation.
  • Advanced data structures with the tibbles of tidyverse and the complete syntax of maggrit that accelerates and enhances the syntax to avoid creating intermediate variables in our data science work thanks to its pipes.
  • Loading data by reading files of all kinds thanks to readr, the improved reading version of tidyverse that streamlines and accelerates the loading of millions of data directly with an instruction, regardless of the type of file: CSV, XML, JSON ...
  • Special data processing libraries such as stringr or lubridate special for specific data formats, as well as to make a regular expression syntax that helps to process complex strings of texts such as tweets or comments from a blog among others.
  • Work in depth with all the essential data types for an analyst: from logical values, integers, doubles, strings, date, datetimes ... We will even see the most common data structures including vectors, lists or tibbles among others .
  • Functional programming vs. imperative programming. The advantages of each of them and when to use one or the other when playing.
  • Model building and updating, the final phase of the data analyst that everyone seeks to solve their original problem.
  • Reporting and how to write recommendations, updates and final reports that allow you to get paid at the end of your work as a Data Scientist.

And much more in this complete Tidyverse course, where the idea is to train you as a data analyst and be able to dedicate yourself in the future to being a well-paid data scientist with a lot of work in the future.

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