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