Data Science and AI in Energy Systems

3 credits · Undergraduate Programs

Applications of data science, machine learning, artificial intelligence and optimization in energy systems. Review of statistics, probability and data science concepts; confidence factors and error analysis. Supervised and unsupervised learning in python including regression and clustering; data engineering for data filtering and feature selection; optimization. Focus on application to problems in the energy industry. Prerequisite(s): Digital Engineering 319 and Chemical Engineering 307.