Introduction to Data Science

- Effective data visualizations
- Summarizing, sorting, subsetting, merging data
- Programming essentials
- Exploratory Data Analysis
- Topics in classification and clustering
- Maps and interactive graphics
- Social Media Data Analytics

Course Description

Learn how to work through data science problems within the statistical programming language R. The course covers the complete analytical process, from getting the data, to applying appropriate exploratory and statistical analysis, and communicating the results. R is free, open-source, and one of the most widely used programming languages in data analytics.

Textbook: R for Data Science, by Hadley Wickham
ISBN-13 (Print version): 978-1491910399 (O’Reilly)
Book also available online free of charge at

Reinaldo (Rei) Sanchez-Arias
Assistant Professor of Data Science