Description

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Joseph Yeates & John Lee – R Fundamentals – CFI Education

R Fundamentals

Start your hands-on data science journey by coding in R

• Explore the foundations of Base R
• Structure projects in RStudio IDE
• Import, clean, transform, and visualize your data in R

Overview
R Fundamentals Course Overview

Start your hands-on data science journey by coding in R programming language. In this course, you’ll progress from coding with Base R to creating a full data science project with Tidyverse packages in RStudio. You’ll begin this course by exploring the foundations of Base R to generate outputs, create variables, and conduct statistical analysis. We’ll then expand on the functionality of analysis by importing Tidyverse packages and structuring our project in RStudio IDE. As we progress, you’ll learn to import, clean, transform, and visualize data for your project, following the data science process taught in our BIDA program.

R Fundamentals Learning Objectives

Upon completing this course, you will be able to:

• Write R code to generate outputs, create variables, and conduct statistical analysis
• Apply best practices to manage our coding workflow
• Structure data sets, scripts, and outputs to create a shareable project in RStudio
• Import and clean our data using Tidyverse packages (e.g., readr and tidyr)
• Transform and visualize our data using Tidyverse packages (e.g., dplyr and ggplot2)

Who Should Take This Course?

This R Fundamentals course is perfect for anyone who would like to build up their programming skills and use R or Python for data science to analyze data. This course is designed to equip anyone who desires to begin or further their career in data analysis, quantitative analysis, business intelligence, or other areas of business and finance.

What you’ll learn

Introduction

Course Introduction
What is R
Learning Objectives
Download Learner Files
Install R & RStudio

Base R

Chapter Introduction – base R
Operators
Variables & Data Types
Data Structures
Math Functions
Statistical Analysis
Packages

RStudio & Tidyverse

Chapter Introduction – RStudio & Tidyverse
RStudio IDE
Install & Load Packages
Tidyverse
Tibbles, Pipes, & Cheat Sheets
Projects in RStudio

Import & Tidy Data

Chapter Introduction – Import & Tidy Data
Import Data with RStudio
Import Data with readr and readxl
Exercise – Import Data
Tidy Data – separate() & unite()
Exercise – separate() & unite()
Tidy Data – Functional Programming
Exercise – Functional Programming
Tidy Data – drop_na() & replace_na()
Tidy Data – pivot_wider() & pivot_longer()
Exercise – pivot_wider() & pivot_longer()
Tidy Data – fill()
Chapter Review – Import & Tidy Data

Transform & Analyze Data

Chapter Introduction – Transform & Analyze Data
Select Columns with select() & pull()
Filter Rows with filter() & slice()
Exercise – select() & filter()
Create New Columns with mutate()
Exercise – mutate()
Group & Aggregate Data with group_by() & summarise()
Exercise – group_by() & summarise()
Nesting Data with nest()
Combining Data with joins()
Select Columns with Tidy Selection
Exercise – Tidy Selection
Perform Multiple Operations with rowwise() & across()
Exercise – rowwise() & across()
Chapter Review – Transform & Analyze Data

Visualize Data

Chapter Introduction – Visualize Data
ggplot2 – Basics
Plot Basics with ggplot2
Exercise – Plot Basics
Geoms
Plot Aesthetics
Exercise – Plot Aesthetics
Layer Geoms
Exercise – Layer Geoms
ggplot2 – Continued
Plot Faceting
Themes
Labels & Legends
Exercise – Facets & Labels
Stats
Scales
Chapter Review – Visualize Data

Course Conclusion

Summary of R Fundamental

Qualified Assessment

Qualified Assessment

This Course is Part of the Following Programs

Why stop here? Expand your skills and show your expertise with the professional certifications, specializations, and CPE credits you’re already on your way to earning.

What our students say

Enjoyed it
Perfect crash course

Micah Othino

Engaging
Insightful to learn about R

Olusegun Akinlolu

Great to learn
A good amount of basic understanding provided.

Firdaus Jahan

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