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.

 The course covers fundamental concepts and issues involved in the design and operations of warehouses and distribution centers. More specifically, the course aims to equip you with the skill to use analytical models and warehouse organizing principles to solve industry problems. There will be occasional visits to the class by speakers from industry, and you will work on a real-world project.

An overview of the foundations and algorithms for solving nonlinear continuous optimization problems with special emphasis on the applications to machine learning and artificial intelligence.

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

Topics include modeling with networks and graphs; linear, nonlinear, and integer programming, construction of models employing modern modeling languages; and general solution strategies.

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

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