Data Science and Machine Learning for CO2 Applications

3 credits · Graduate Programs

Introduces Machine Learning concepts, types, and workflow of a typical ML project. Popular ML libraries, supervised learning algorithms, unsupervised learning algorithms, representing data and engineering features, model evaluation and improvement. Application to problems in carbon capture, utilization and storage. Prerequisite(s): Admission to the Graduate Certificate in Advanced Engineering Practice I or II, with a specialization in Carbon Capture, Utilization, and Storage.