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Earn Your R Certificate

If you complete this class, you'll be issued a digital completion certificate. Our certificates are shareable, unique, blockchain verified and independently verifiable.

Prerequisites & Suitability

Check the requirements below before considering this course.

  • First Timers

    This course teaches R from the basics, so no programming experience is required to take this class. That being said, you will benefit most if you already have a strong foundation in mathematics and statistics.

  • Junior Engineers

    R is a great choice as a 2nd programming language. If you're already well versed in a general-purpose language, then you'll be able to appreciate how well-suited R is to statistical analysis and data science.

  • Senior Engineers

    If you already have a strong foundation in R or Data Science in general, then this course may be review for you. Please review the curriculum below to make sure we're covering topics that interest you.

Course Curriculum

41 Lectures, 10 Homeworks, 3 Large Projects

  • 1
    Course Overview
    • Introduction
    • Table of Contents
    • Download RStudio
  • 2
    Data Types
    • Introduction to Variables - Part A
    • Introduction to Variables - Part B
    • Homework #1: Variables
  • 3
    Input & Output (I/O)
    • Data Input - Part A
    • Data Input - Part B
    • Data Output
    • Homework #2: I/O
  • 4
    Control Flow
    • Loops
    • If Statements - Part A
    • If Statements - Part B
    • Homework #3: Control Flow
  • 5
    Core Concepts in R
    • Vectors
    • Functions - Part A
    • Functions - Part B
    • Packages - Part A
    • Packages - Part B
    • Case Study - Part A
    • Case Study - Part B
    • Homework #4: Functions
    • Project #1
  • 6
    Matrices
    • Introduction to Matrices
    • Homework #5: Matrices
  • 7
    Data Frames
    • Introduction to Data Frames - Part A
    • Introduction to Data Frames - Part B
    • Homework: #6: Data Frames
  • 8
    Lists
    • Introduction to Lists and lapply - Part A
    • Introduction to Lists and lapply - Part B
    • Homework #7: Lists
  • 9
    Data Analysis
    • Data Manipulation and dplyr - Part A
    • Data Manipulation and dplyr - Part B
    • Data Manipulation and dplyr - Part C
    • Homework #8: Data Analysis
  • 10
    Data Visualization with ggplot
    • Basic Plots - Part A
    • Basic Plots - Part B
    • Additional Plotting - Part A
    • Additional Plotting - Part B
    • Advanced Plotting - Part A
    • Advanced Plotting - Part B
    • Homework #9: Visualizations
    • Project #2
  • 11
    Machine Learning
    • Introduction to Machine Learning - Part A
    • Introduction to Machine Learning - Part B
    • Introduction to Machine Learning - Part C
    • K-means Clustering - Part A
    • K-means Clustering - Part B
    • K-means Clustering - Part C
    • Decision Trees - Part A
    • Decision Trees - Part B
    • Decision Trees - Part C
    • Conclusion
    • Homework #10: Decision Trees
    • Project #3 (Final Exam)
  • 12
    Completion Certificate
    • How to Get Your Certificate