Data Analytics for Complexity Science

Catalog description

A fundamental characteristic of complex adaptive systems (CAS) is the multi-dimensional interconnections among system components. Understanding these systems requires methods to represent and analyze CAS data. Introduces methods to manage, describe, visualize, compare and communicate data about CAS. Enables students to learn how to apply diverse quantitative approaches to CAS data (including a variety of data management, statistical and graphical methods). Strongly application oriented and hands-on. Because managing and analyzing data for CAS normally requires the use of computational tools, students use one of the world's leading platforms for data science in this course, R.