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