CVEEN6115

The proliferation of data from a variety of sources (embedded sensor networks, UAVs, social media) and the development of algorithms for the large-scale analysis of and prediction from these data has far-reaching applications across Civil and Environmental Engineering (CVEEN) disciplines. Examples include developing image-recognition systems for identifying structural damage, text, and image classification tools understanding citizen sentiment in “smart cities,” improved classification systems for early-warning systems, and real-time mapping of environmental data from embedded and remote sensors. This course introduces applications of data science and machine learning concepts to civil and environmental engineering problems through interactive coding-based lectures, and a final project based on the student’s research. Prerequisites: Graduate-level standing (MS or Ph.D.). Senior-level undergraduate students may also enroll with sufficient background, GPA, and instructor approval. Students must have completed undergraduate courses in probability and statistics, multivariate calculus, and linear algebra.

Prerequisites: Graduate Standing OR Department Consent

Spring