Data analytics: that is the examining raw data with the purpose of drawing conclusions about that information. The unit will cover the techniques and methods of collecting data, designing data structures, analysis of data and science-based inference from data. These will be developed through real-world transport operations using available data bases and case studies of urban transport situations. Students will be introduced to relational databases - enabling them to store, manage and retrieve data. Subsequently, they will study the tools to create algorithms to process raw data, retrieve data from APIs and merge datasets to make them useable for a variety of transport analyses including statistical modelling and spatial analysis.
through semester assessment (70%), final exam (30%)
MATH1005 AND CIVL2700. Understanding of statistical inference. Familiarity with the urban transport network and basic concepts in transport studies.