Supercharge your data analysis

  • Get to grips with data cleaning methods
  • Explore statistical concepts and programming in R, including best practices
  • Build a data science project with real-world examples
  • Optional: 2 Hours of individual coaching
  • Receive a Certificate of Achievement

What you will learn

R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. To start with, you'll understand you how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops. Once you have grasped the basics, you'll move on to studying data visualization and graphics. You'll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you'll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values. By the end of this course, you'll have completed an entire data science project of your own for your portfolio or blog.

  • Use basic programming concepts of R such as loading packages, arithmetic functions, data structures, and flow controldepending on your needs

  • Import data to R from various formats, such as CSV, Excel, and SQL

  • Clean data by handling missing values and standardizing fields

  • Perform uni-variate and bi-variate analysis using ggplot2

  • Create statistical summary and advanced plots, such as histograms, scatter plots, box plots, and interaction plots

  • Apply data management techniques, such as factors, pivots, aggregation, merging, and dealing with missing values, on the example data sets

Course description

Why learn R Programming Fundamentals?


Why Wait? Enroll Now to start programming with R

Create visually appealing plots

Create statistical summary and advanced plots such as histograms, scatter plots, box plots, and interaction plots.


  • Activities

    Hands-on activities enabling learners to practice what is learned in the course.

  • Self-paced learning

    The course is available 24/7, allowing you to take the course on your own time and at your own pace.

  • Support

    Our team will help resolve any issues that occur during and after the course.

Your course includes

  • 3 hours of self-paced videos

  • Access to 2 hours of live data labs

  • Practical Activities

  • Certificate of Achievement

  • Suggested readings for each topic

  • Lifetime access to self-paced learning

Course curriculum

  • 1

    Introduction to R

    • Course Overview FREE PREVIEW
    • Installation and Setup
    • Lesson Overview
    • Using R, RStudio, and Installing Useful Packages
    • Activity 1-1: Installing the Tidyverse Packages
    • Variable Types and Data Structures: Variable Types
    • Activity 1-2: Identifying Variable Classes and Types
    • Activity 1-3: Creating Vectors, Lists, Matrices, and Dataframes
    • Data Structures
    • Basic Flow Control
    • Activity 1-4: Building Basic Loops
    • Data Import and Export
    • Activity 1-5: Exporting and Importing the mtcars Dataset
    • Getting Help with R
    • Activity 1-6: Exploring the Introduction to dplyr Vignette
    • RStudio Community, Stack Overflow, and the Rest of the Web
    • Lesson Summary
    • Quiz
  • 2

    Data Visualizations and Graphics

    • Introduction to Data Visualization and Graphics FREE PREVIEW
    • Creating Base Plots
    • Factor Variables
    • Titles and Axis Labels
    • Activity 2-1: Recreating Plots with Base Plot Methods
    • ggplot2: Introduction
    • ggplot2: Histogram
    • ggplot2: Scatterplots and boxplots
    • Activity 2-2: Recreating Plots Using ggplot2
    • ggplot2: Digging in aes(), and Facet Wrapping and Gridding
    • ggplot2: Boxplot + coord_flip() and Adding Titles and Axis labels to ggplot2
    • Activity 2-3: Utilizing ggplot2 Aesthetics
    • Interactive Plots
    • Lesson Summary
    • Quiz
  • 3

    Data Management

    • Lesson Overview
    • Factor Variables
    • Activity 3-1: Creating and Manipulating Factor Variables
    • Summarizing Data
    • Activity 3-2: Creating Data Summarization Tables
    • Activity 3-3: Implementing Data Summary
    • Splitting and Combining Datasets
    • Activity 3-4: Demonstrating Splitting and Combining Data
    • Merging and Joining Datasets
    • Activity 3-5: Merging and Joining Data
    • Lesson Summary
    • Quiz
  • 4


    • Lesson Files
  • 5

    Activity Solutions

    • 1: Introduction to R
    • 2: Data Visualization and Graphics
    • 3: Data Management

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  • What if I have questions after I complete the course?

    We will address queries during and after the course.

  • How soon after enrolling will I get access to the content?

    The LMS access will be available instantly, and you will be able to access the all of the course videos, activities, and lesson labs.

  • Is the course material accessible to the students even after the course training is over?

    Yes, once you have enrolled in the course, you will have lifetime access to the course material.

  • What are the payment options?

    Payments can be made using any major credit card available and a receipt will be issued to you automatically via email.