Introduction to R and Visualization

Sample video: A data scientist's approach

Introduction to R and Visualization


Learn what data science is and how it is used by organizations large and small


Learn how to use R to transform, format, and clean gigabytes of data in seconds


Create expressive visualizations with R combining many variables in detailed charts

Instruction2 hours 40 minutes
Practice 20+ hours

Syllabus: Introduction to R and Visualization

This course teaches students a new skill set in under 3 hours of instructional video. It’s designed for individuals without a math or programming background and walks them step-by-step through basic data analysis techniques and visualization skills.

By the end of this course, students will be able to:
  1. Think about data and manipulate it
  2. Code and format data in R
  3. Create dynamic and appealing visualizations with R
  1. Concept reviews: these are comprised of short five question quizzes that cover the most important concepts and ideas in each lesson. They encourage holistic understanding and are multi-faceted ques=on types (i.e. drag and drop, fill-in-the-blanks, matching, etc).
  2. Exercises: these are additional videos that cover the coding functions in the instructional video in more depth. They are project-based and include coding templates for students to strengthen their skills outside of the course.
Materials provided:
  1. Accompanying PDFs to use as reference materials
  2. R code templates from the instructional videos and exercises
  3. Data sets used in the instructional videos and exercises

Course Outline

1. Getting started with R (6 min)

Installing R and RStudio
Introduction to RStudio

2. Overview of data science and R (31 min)

What is data science?
A data scientist’s approach
Introduction to R
Getting started in R

3. Working with data in R (37 min)

Understanding data types
Manipulating data
Subsetting data
Summarizing data

4. Basic visualizations (38 min)

Basic plotting in R
Basic plotting in ggplot2
Building a graph
Customizing graphs
Creating a heatmap

5. Advanced visualizations (27 min)

Advanced plotting in ggplot2
Advanced plotting, part 2
3D plotting

6. Visualizing data with the Google API (21 min)

Mapping DC crime
Creating reusable functions
Tips and additional resources

Total instruction time: 2 hrs, 40 min

Dr. Harlan Harris

Harlan Harris is the Director of Data Science at the Education Advisory Board, and the co-founder of the Data Science DC Meetup and Data Community DC, Inc. Dr. Harris has many years in the data science industry and co-authored “Analyzing the Analyzers” through O’Reilly Media.

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