
Explore the foundations of statistics for R, distinguishing descriptive and inferential statistics, and learn how data types, populations, samples, parameters, and histograms guide analysis.
Learn to write and save R scripts in RStudio, create new scripts, run code from the editor and console, and assign values to variables.
Learn to create and knit an R Markdown report in RStudio by combining narrative text, code, and plots into an HTML document. Load tidyverse to summarize data and generate plots.
Learn to import data into R from CSV and Excel using tidyverse and read_csv/read_excel. View, summarize, and inspect structure with the environment pane to explore datasets.
Clean messy data in R with dplyr and tidyverse by standardizing names, trimming spaces, converting empty strings to na, and filtering out missing grades.
Learn to save your plots as image files and export data frames as spreadsheets using ggsave and write.csv, while organizing outputs with folders and file paths for easy sharing.
Transform data between wide and long formats using pivot longer and pivot wider in R with tidyverse, enabling ggplot2 visualization, modeling, and clean reporting.
Visualize group summaries in R with bar charts to compare average scores across subjects and classes, using error bars for spread from minimum to maximum, standard deviation, and confidence intervals.
Master RStudio by learning how to save plots as PNG or PDF and export summaries as CSV, using ggsave and getwd to manage files from the mtcars data.
Are you ready to start your journey into data analysis?
This beginner-friendly course will teach you how to use RStudio from scratch, even if you have never coded before. This course will help you whether you're a student, a professional, or a future data scientist, you'll get hands-on practice working with real datasets, writing R scripts, cleaning messy data, and creating powerful visualizations.
Each section builds your skills step-by-step:
Section 1: Gives an introduction to RStudio and what you can achieve with it.
Section 2: Focuses on learning the basics: how to run scripts, install packages, create variables, and navigate RStudio's environment.
Section 3: Dives into functions, working with data frames, and creating your first plots and R Markdown reports.
Section 4: Brings your skills together by learning how to import, clean, summarize, and visualize real-world data.
Section 5: You'll advance your toolkit with filtering, combining datasets, pivoting data, and making polished summaries and visualizations.
By the end of this course, you'll have the confidence to analyze data, create visual reports, and present your results using RStudio!
Who this course is for
Absolute beginners who want to learn R and RStudio
Students and researchers needing basic data analysis skills
Professionals working with data who want to add RStudio to their skill set
Anyone interested in data science, data visualization, or reporting
Requirements
No prior R or programming experience required!
A computer with internet access to install R and RStudio (free software)
A willingness to learn by doing — we’ll walk through everything together!
Course Sections Overview
Section 1: Introduction
Get an overview of the course and how RStudio can supercharge your data projects.
Section 2: Basic Functions
Explore RStudio, run your first scripts, and master variables, vectors, and environments.
Section 3: Manipulate Variables, Vectors and Data
Dive into variables, vectors and data manipulation and working with and viewing data.
Section 4: Functions and Data Frames
Learn to use functions, work with data frames, and build basic visualizations with ggplot2.
Section 5: Working with Datasheets
Import, clean, summarize, and visualize real datasets from Excel and CSV files.
Section 6: Advanced Data Wrangling and Visualization
Take your skills further with data filtering, combining datasets, pivoting tables, and creating faceted plots.
Why Take This Course?
Clear, beginner-friendly explanations
Hands-on practice with real-world data
Step-by-step screen demonstrations
Practical examples and guided exercises
Skills you can immediately apply in school, work, or projects
You can Enroll today and start mastering RStudio with confidence!