5. 1.5 Lecture Hour. Fundamental concepts and methods applied in data science, focusing on energy applications; topics include probability theory, probability distributions, statistical data modeling and inference, linear regression and predictive models, time series forecasting, dimension reduction, introduction to machine learning, and implementation of algorithms. Credit 1.
5. 1.5 Lecture Hour. Fundamental concepts and methods applied in data science, focusing on energy applications; topics include probability theory, probability distributions, statistical data modeling and inference, linear regression and predictive models, time series forecasting, dimension reduction, introduction to machine learning, and implementation of algorithms. Credit 1.
