As part of Harvard University's Professional Certificate Program in Data Science, this course covers the basics of data visualization and exploratory data analysis. It will use three motivating examples and ggplot2, a data visualization package for the statistical programming language R. You will start with simple datasets and then graduate to case studies about world health, economics, and infectious disease trends in the United States.
You will be looking at how mistakes, biases, systematic errors, and other unexpected problems often lead to data that should be handled with care. The fact that it can be difficult or impossible to notice a mistake within a dataset makes data visualization particularly important.
The growing availability of informative datasets and software tools has led to increased reliance on data visualizations across many areas. Data visualization provides a powerful way to communicate data-driven findings, motivate analyses, and detect flaws. This course will give you the skills you need to leverage data to reveal valuable insights and advance your career.
Topics of study
Data visualization principles
How to communicate data-driven findings
How to use ggplot2 to create custom plots
The weaknesses of several widely used plots and why you should avoid them
About Harvard University
Harvard University is devoted to excellence in teaching, learning and research, and to developing leaders in many disciplines who make a difference globally. Harvard faculty are engaged with teaching and research to push the boundaries of human knowledge. The University has 12 degree-granting schools in addition to the Radcliffe Institute for Advanced Study.
Established in 1636, Harvard is the oldest institution of higher education in the United States. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment of over 20,000 degree candidates, including undergraduate, graduate and professional students. Harvard has more than 360,000 alumni around the world.