Data science for networks

Professors: Luca Vassio

Official description of the course: here

In this course, we will explore data analysis and prediction topics using complex network datasets. In particular, our focus will be on temporal and structural data. We will exploit real complex networks from popular repositories. The course will cover the following topics: introduction to network science, probabilistic network models, graph visualization techniques, random walks over graphs, cascades and time series. During each class, we will see examples using Python programming language and each student will execute some small programming assignment and data analysis and visualization, possibly using data from their personal research.


• Intro to network science • Algorithms over graphs • Graph visualization techniques • Random walks • Probabilistic network models • Cascades and time series