Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression, and analysis of variance. Crosslisted with MATH 3770 and CEE 3770. Also, credit not awarded for both ISYE 3770 and MATH 3670.

Covers modeling of discrete-event dynamic systems and introduces methods for using these models to solve engineering design and analysis problems.

An introduction to important and commonly-used models in analytics, as well as aspects of the modeling process.

Covers modeling of discrete-event dynamic systems and introduces methods for using these models to solve engineering design and analysis problems.

Theoretical/computational foundations of analyzing large/complex modern datasets, including the fundamental concepts of machine learning and data mining needed for both resesarch and practice. Crosslisted with CSE 6740. Credit not awarded for both ISYE 6740 and CS 4641/7641/CSE 6740.

 This course focuses on analysis of high-dimensional structured data including profiles, images, and other types of functional data using statistical machine learning. A variety of topics such as functional data analysis, image processing, multilinear algebra and tensor analysis, and regularization in high-dimensional regression and its applications including low rank and sparse learning is covered. Optimization methods commonly used in statistical modeling and machine learning and their computational aspects are also discussed. 

This course focuses on analysis of high-dimensional structured data including profiles, images, and other types of functional data using statistical machine learning. A variety of topics such as functional data analysis, image processing, multilinear algebra and tensor analysis, and regularization in high-dimensional regression and its applications including low rank and sparse learning is covered. Optimization methods commonly used in statistical modeling and machine learning and their computational aspects are also discussed. 

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

Human Systems Integration Analysis and Synthesis, a PMASE complex systems elective, ensures human-related technical issues are properly addressed during system definition, design, development, and implementation.