Applied Social Network Analysis in Python

University of Michigan

data-analysis   |   Advanced   |   14 Hours

This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem.

This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python.

What skills will you gain?

Network Analysis

social network analysis

Graph Theory

social network

analysis

network theory

Human Learning

Computer Programming

Python Programming

graphs