Data Science with R Tidyverse

Data Science with R Tidyverse, available at $49.99, has an average rating of 4.45, with 26 lectures, based on 76 reviews, and has 272 subscribers.

You will learn about Learn how to improve your R programming skills and code efficiently Learn how to use powerful tidyverse tools to tackle everyday data science problems Learn how to manipulate data with dplyr Learn how to re-shape and re-organise data with tidyr Learn how to create advanced graphics using ggplot2 Learn how to link code efficiently using the magrittr forward pipe (%>%) Realistic worked examples to illustrate the tools of the tidyverse Mini quizzes to test your knowledge of the tidyverse functions This course is ideal for individuals who are Beginners in R looking to explore the tools of the tidyverse or Intermediate users of R looking to code more efficiently It is particularly useful for Beginners in R looking to explore the tools of the tidyverse or Intermediate users of R looking to code more efficiently.

Enroll now: Data Science with R Tidyverse

Summary

Title: Data Science with R Tidyverse

Price: $49.99

Average Rating: 4.45

Number of Lectures: 26

Number of Published Lectures: 26

Number of Curriculum Items: 26

Number of Published Curriculum Objects: 26

Original Price: £19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn how to improve your R programming skills and code efficiently
Learn how to use powerful tidyverse tools to tackle everyday data science problems
Learn how to manipulate data with dplyr
Learn how to re-shape and re-organise data with tidyr
Learn how to create advanced graphics using ggplot2
Learn how to link code efficiently using the magrittr forward pipe (%>%)
Realistic worked examples to illustrate the tools of the tidyverse
Mini quizzes to test your knowledge of the tidyverse functions

Who Should Attend

Beginners in R looking to explore the tools of the tidyverse
Intermediate users of R looking to code more efficiently

Target Audiences

Beginners in R looking to explore the tools of the tidyverse
Intermediate users of R looking to code more efficiently

Take your R programming skills to the next level with this short course in data science using R’s tidyverse packages! Learn to code efficiently and elegantly to tackle everyday data science challenges in business, finance, scientific research, engineering and more!

Do you feel you have a basic knowledge of R but don’t yet have the tools or confidence to tackle everyday data science problems like plotting, summarising, sub-setting and merging data? Still turning to MS Excel to manipulate, format, and visualize data? Then look no further.

Aimed at beginners and intermediates who have a basic understanding of R, this course introduces some of the core tools of the tidyverse. It covers a step-by-step guide to the most important functions offered by some tidyverse packages, providing students with a comprehensive toolkit to address everyday data science tasks.

The course covers the following areas:

1) Data manipulation with dplyr (filtering, sorting, creating new variables, summarising data, joining data sets, selecting columns/rows)

2) Data reformatting with tidyr (gathering variables, spreading out variables, separating data in cells)

3) Data visualization with ggplot2 (scatterplots, boxplots, bar charts, line charts, panels, adding errorbars)

4) Linking code efficiently using the magrittr forward pipe operator

After completing the course, you will be confident to use R for your everyday data science tasks!

Course Curriculum

Chapter 1: Welcome

Lecture 1: Introduction

Chapter 2: Data manipulation with dplyr

Lecture 1: Filtering data

Lecture 2: Selecting variables in data

Lecture 3: Extracting rows in data

Lecture 4: Creating new variables from data

Lecture 5: Sorting data

Lecture 6: Grouping variables

Lecture 7: Summarising data

Lecture 8: Magrittr forward pipe (%>%)

Lecture 9: Joining or merging several data sets

Lecture 10: Additional dplyr tips

Chapter 3: Data re-shaping with tidyr

Lecture 1: Introducing tidy data

Lecture 2: Gathering variables

Lecture 3: Spreading variables

Lecture 4: Separating values within a cell

Chapter 4: Data visualisation with ggplot2

Lecture 1: Principles of a ggplot function call

Lecture 2: Creating scatterplots

Lecture 3: Creating boxplots

Lecture 4: Creating barcharts

Lecture 5: Creating line charts

Lecture 6: Creating a panel of graphs

Lecture 7: Additional ggplot2 tips

Lecture 8: Advanced formatting in ggplot2

Lecture 9: Errorbars

Chapter 5: Importing and exporting with R

Lecture 1: Working with excel and csv files

Lecture 2: Working with Google Sheets

Instructors

Adam Hayward
Scientist

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 4 votes
4 stars: 27 votes
5 stars: 43 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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