CUSP-GX 5002 Principles of Urban Informatics

3 Credits

This course builds the foundation of the skills and tools necessary to address urban analytics problems with urban data. It starts with basic computational skills, statistical analysis, good practices for data curation and coding, and further introduces a machine learning paradigm and a variety of common supervised and unsupervised learning tools used in urban informatics, including regression analysis, clustering and classification. After this class you should be able to formulate a question relevant to Urban Informatics, locate and curate an appropriate data set, identify and apply analytic approaches to answer the question, obtain the answer and assess it with respect to its certainty level as well as the limitations of the approach and the data. The course will also contain project-oriented practice in urban informatics, including relevant soft skills - verbal and written articulation of the problem statement, approach, achievements, limitations and implications.