CHE 523Introduction to Machine Learning and Data Science

This course provides an overview of the theory, methods, and application of data science and machine learning to analyze data sets arising in applications/industries of importance to chemical engineers. Course topics focus on data representation (i.e., feature engineering), unsupervised learning, supervised learning, and introductory deep learning using techniques/models such as data scaling, principal component analysis, support vector machines, Gaussian processes, Lasso regression, decision trees, and neural networks. Applications include (but are not limited to) experimental data analysis, process monitoring, surrogate modelling, and thermophysical property prediction. The use of relevant computing tools will be emphasized.