1 - Graphs
1.1 - Graph theory, historical introduction, and examples
1.2 - Directed and weighted graphs; bipartite graphs; adjacency matrix
1.3 - Degree, mean degree, and degree distribution
1.4 - Topological concept on graphs: distance, minimal connecting path, diameter
1.5 - Centrality measures; cliques, motifs, and communities
1.6 - Types of networks: random, small-world, scale-free
2 - Social networks
2.1 - Definition and context
2.2 - Local and global properties of social networks
2.3 - Comparison with other networks
2.4 - Social mechanisms
2.5 - Applications of social networks
3 - Graph/social network analysis
3.1 - Creating a graph
3.2 - Graph analysis
3.3 - Graph simulation
3.4 - Statistical tests
3.5 - Practical examples
4. Practical examples of graph analysis
4.1 Link prediction: application to friend recommendation
4.2 Epidemic models in networks
4.3 Build, analyze and visualize information networks
4.4 Analysis and visualization of dynamic networks
5. Introduction to data visualization
5.1 Data types and sources
5.2 Main tools to visualize data
5.3 Data reduction techniques
5.4 Static an dynamic data visualization
5.5 Graph data
5.6 Prtactical examples