Stony Brook University 3 credits CIV
An introductory course on practical applications and challenges of sensing, data analytics and machine learning in the context of physical urban systems. Background is provided on data analysis and associated challenges specific to smart cities applications, insights behind signal representation, statistical modeling, and machine learning, and critical interpretation of outcomes. The course is suitable for students without prior experience in probabilistic and statistical modeling, or working with data. Topics include data visualization, noise cleansing, frequency domain analysis, forward and inverse modeling, feature extraction, sampling bias, statistical modeling, machine learning, and error analysis. 3 credits Grading Letter graded (A, A-, B+, etc.)
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