This course provides a comprehensive introduction to Social Network Analysis (SNA), including the computation of structural characteristics, analysis of ego and complete networks, position and role analysis, and statistical methods for hypothesis testing in network contexts. Foundational topics such as centrality measures, community detection, and network visualization are covered in depth. Building on this foundation, the course introduces students to contemporary developments in network science, with a particular emphasis on Graph Neural Networks (GNNs). Applications range from social influence prediction to recommendation systems and link prediction. Prerequisite: INSY 5339.