Engineering Data Analytics

Data-driven decision-making is an essential component of emerging engineering systems that generate and consume very large amounts of sensing data from autonomous vehicles to digital pathology. This course covers technologies and methodologies necessary for inferring useful information and identifying underlying patterns from often raw, incomplete, noisy and corrupted data that is present in real-life applications. It will also give students the opportunity to explore advanced solutions of data analytics such as dimensionality reduction, sparse encoding, compressive sensing, nonlinear filtering, manifold learning, and generative data modelling.