Process Data Analytics

Undergraduate

covers all necessary elements, beginning from data collection to model development, to conduct a data analysis project in a process plant. The course focuses on data quality evaluation and preprocessing of data to ensure the fidelity of data. A range of unsupervised techniques including several variants of principal component analysis (PCA), support vector machine (SVM) and clustering algorithms will be covered. Students will also receive hands on training on various Matlab toolboxes and Python libraries.