Introduction to R Programming – A Modern Approach

Introduction to R Programming – A Modern Approach, available at $79.99, has an average rating of 4.75, with 42 lectures, based on 111 reviews, and has 468 subscribers.

You will learn about Basics of R programming Data wrangling manipulations Make use of the tidyverse packages which includes but not limited to purrr, dplyr, ggplot2, etc.. Create pipelines using the pipe operator to chain instruction and transform a data frame to another Transform data frames then pipe them to ggplot for EDA or professional looking graphs Showcase the importance of a working directory Teach the fundamentals of R – useful beyond this course Understanding functions and how to use existing ones or how to create your own Modern techniques used in R programming by data scientists Install and load packages such as lubridate, readxl, esquisse, etc… Read and write different types of data Group and summarize data using the dplyr verbs Transpose data with dplyr pivoting functions or using the soon to be deprecated gather and spread functions This course is ideal for individuals who are Aspiring data scientists, statisticians, or data analyts or Beginner R programming developers curious about data science or Non computer programmers who are willing to learn a fun, useful, and intuitive coding language or Data scientists eager to learn R programming It is particularly useful for Aspiring data scientists, statisticians, or data analyts or Beginner R programming developers curious about data science or Non computer programmers who are willing to learn a fun, useful, and intuitive coding language or Data scientists eager to learn R programming.

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Summary

Title: Introduction to R Programming – A Modern Approach

Price: $79.99

Average Rating: 4.75

Number of Lectures: 42

Number of Published Lectures: 42

Number of Curriculum Items: 42

Number of Published Curriculum Objects: 42

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will Learn

• Basics of R programming
• Data wrangling manipulations
• Make use of the tidyverse packages which includes but not limited to purrr, dplyr, ggplot2, etc..
• Create pipelines using the pipe operator to chain instruction and transform a data frame to another
• Transform data frames then pipe them to ggplot for EDA or professional looking graphs
• Showcase the importance of a working directory
• Teach the fundamentals of R – useful beyond this course
• Understanding functions and how to use existing ones or how to create your own
• Modern techniques used in R programming by data scientists
• Install and load packages such as lubridate, readxl, esquisse, etc…
• Read and write different types of data
• Group and summarize data using the dplyr verbs
• Transpose data with dplyr pivoting functions or using the soon to be deprecated gather and spread functions

Who Should Attend

• Aspiring data scientists, statisticians, or data analyts
• Beginner R programming developers curious about data science
• Non computer programmers who are willing to learn a fun, useful, and intuitive coding language
• Data scientists eager to learn R programming

Target Audiences

• Aspiring data scientists, statisticians, or data analyts
• Beginner R programming developers curious about data science
• Non computer programmers who are willing to learn a fun, useful, and intuitive coding language
• Data scientists eager to learn R programming