Courses in special topics of timely interest to the profession, conducted by resident or visiting faculty.

Design principles, one-way and two-way layout models, analysis of variance, full and fractional factorial designs at two levels, response surface methodology, robust parameter design for production/process improvement, and computer experiments.

Basic forecasting methods, ARIMA models, transfer functions.

Senior design project requiring student to formulate a project plan with an off-campus enterprise. Includes specific milestones, targets, and evaluation criteria.

An introduction to some commonly used data mining and statistical learning algorithms, such as the K-nearest neighbor (KNN) algorithm, linear methods for regression and classification, tree-based methods, ensemble methods, support vector machine, neural networks, and the K-means clustering algorithm.

Examines energy production, use, and production, use, and policy using quantitative engineering and policy analysis. Addresses resource constraints, physical principles, and policy analysis methods.

Topics include conditional probability, density and distribution functions from engineering, expectation, conditional expectation, laws of large numbers, central limit theorem, and introduction to Poisson Processes.