Independent research conducted under the guidance of a faculty member.

This course provides academic credit for independent thesis research conducted under the supervision of a Georgia Tech faculty advisor. The course does not involve regular class meetings, assignments, or examinations. The scope and direction of research are determined by the student in consultation with the thesis advisor, consistent with the requirements of the degree program.

For graduate students holding graduate research assistantships.

For graduate students holding graduate research assistantships.

Topics include neural networks, support vector machines, classification trees, boosting and discriminant analyses. Intended for Ph.D. students and those seeking the M.S. in Statistics.

Topics include component reliability and lifetime distributions, hazard rates, system reliability, covariate reliability models, state-dependent models, nonparametric models, statistical estimation and inference, maintenance management and repair processes.

An introduction to basic stochastic processes such as Poisson and Markov processes and their applications in areas such as inventory, reliability, and queueing.

Undergraduate research conducted under the guidance of a faculty mentor. This course is a graded academic credit research course.

This course integrates decision and data analytics to solve real-world problems. It includes hands-on system modeling, data collection and analysis, and reporting writing projects.