- Prior knowledge:
- No previous knowledge expected

This tutorial is pre-recorded.

This tutorial will use Python's NetworkX to build your understanding of graph analysis using real world datasets. You'll see how each algorithm and technique can be applied to extract information in practical setting (airline transportation network, bitcoin transaction network, open street map, twitter social network, etc) so that you can quickly deploy them in your own work.

Graphs are simple concepts: a set of individual Nodes (components) connected by Edges (relationships). In this very simplicity lies their power. They can describe the structure of our friendships, connections between airports, the spread of diseases from person to person, the relation of one concept to another, how species interact in an ecosystem or how computers communicate to form the World Wide Web.

Networks are the fundamental language of our increasingly complex world and the key to successfully understand it. By exploring in detail the way graphs can be used to explore, describe, analyze and understand empirical datasets we will put you at the forefront of this growing field.

In this tutorial we will use Python's NetworkX to build our understanding of network representations and algorithms by exploring real world network datasets such as the airline transportation network, the bitcoin transaction network, the road network of open street map, etc. Through this practical approach attendees will better understand the fundamental ideas and concepts that lie at the base of our increasingly complex world and take the first steps towards being at the forefront of this growing field.

The tutorial is split into 4 sections of ~20m each where we learn about specific topics of graph analysis by exploring a real world dataset, from the basic ELT all the way to the final insights and visualizations.