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

Assessment:

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) – Free trial!

Installing R and RStudio
Introduction to RStudio

2. Overview of data science and R (31 min) – Free trial!

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