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R Programming Language, Data Analysis, Data Cleaning, Data Science, Data Wrangling, tidyverse, dplyr, ggplot2, RStudio

What you'll learn?

How to use R's tidyverse libraries in your data science projects

How to write efficient R code for data science related tasks

What is clean data

How to clean your data with R

What is grammar of data wrangling

How to wrangle data with dplyr and tidyr

How to import data into R

How to properly parse imported data

How to chain R's functions into a pipeline

How to manipulate strings

What are Regular Expressions

How to use stringr library with Regular Expressions

How to use forcats library to manipulate categorical variables

What is Grammar of Graphics

How to visualize data with ggplot2 library

What is functional programing

How to use purrr library for mapping functions, nesting data, manipulating lists, etc.

What is relational data

How to use dplyr library for relational data

What is tidy evaluation

How to use tidyverse tools to finish a practical project

- R and RStudio already installed on your computer.
- Basic knowledge of statistics is a plus.
- Basic to intermediate R knowledge is a plus.
- Complete R beginners will find course more challenging.
- For complete R beginners I recommend first taking one of the R beginners courses.
- Interest in data science and data science related tasks.
- Interest in how to write efficient R code.
- Please update R or R's libraries if necessary. List of versions ( R and all R's libraries used in the exercises) provided at the beginning and at the end of course material.

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**Price**Free**Instructor**InstaDotAnalytics**Duration**22 days**Category**Programming Languages**Curriculum**10**Lectures**79**Enrolled**0

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