I will start by introducing some basic concepts of graph

theory (adjacency matrix, paths, degree, clustering...); I will then

introduce some tools which are customarily used for the statistical

characterization of large networks, such as degree distribution,

clustering spectrum, measures of degree correlations. I will give some

examples of application of these tools to real-world networks of

various origins (social networks, infrastructure networks...).

Some modelling frameworks will also be described. If time allows, I

will also give an introduction to the study of dynamical phenomena on

complex networks, such as epidemic spreading