Data collection & preprocessing
Methodologies to gather real-world data and turn it into graphs ready for analysis.
← Teaching
MSc · new course
Advanced Laboratory of Network Science
Hands-on MSc laboratory on building robust pipelines to analyse real-world complex systems represented as graphs: data collection and preprocessing, enriched network models, experimental evaluation and advanced Python libraries.
MSc New
Understanding complex systems, whether social, biological or technological, is essential to tackle many of today’s challenges: reducing polarization and radicalization online, predicting high-frequency financial transactions, or understanding how proteins interact.
Building on the foundations of Social Network Analysis, this laboratory teaches students to design robust pipelines for the analysis of real-world systems represented as graphs. It is strongly hands-on: every concept is practised with advanced Python libraries for network analysis.
What you will learn
Enriched network models
Models that extend the descriptive power and the practical applications of graphs.
Experimental evaluation
Techniques to design experiments and assess their outcomes.