Industrial Engineering (BSIE)

Leading Undergraduate Program in Quantitative Approaches & Modern Methodologies

Designed to develop the technical skills and intellectual discipline needed to become leaders in industrial engineering and related professions, the Industrial Engineering undergraduate program is distinctive in its emphasis on quantitative, economic, and computer-aided approaches to production and service management problems. We focus on providing an experimental and mathematical problem-formulating and problem-solving framework for industrial engineering work, with a broad foundation in the current ideas, models, and methods of industrial engineering.

Electives for the Industrial Engineering Program

The undergraduate Industrial Engineering program requires a total of nine (9) points of technical electives equivalent to three (3) courses.
 

  • ORCA E2500: Foundations of Data Science (only if taken by the end of sophomore year)IEOR E4418: Transportation Analytics and Logistics
  • IEOR E4212: Data Analytics and Python for OR
  • IEOR E4407: Game Theoretic Models for OR (Seniors Only) 
  • IEOR E4507: Healthcare Operations Management
  • IEOR E4511: Industry Projects in Analytics
  • IEOR E4520: Applied Systems Engineering
  • IEOR E4525: Machine Learning for OR & FE
  • IEOR E4526: Analytics on the Cloud
  • IEOR E4530 AI, Games, & Markets
  • IEOR E4540: Data Mining for Engineers (Seniors Only)
  • IEOR E4650: Business Analytics (Junior year Spring or Seniors Only)
  • IEOR E4700: Introduction to Financial Engineering
  • IEOR E4711: Global Capital Markets
  • IEME E4200: Human-Centered Design
  • CIEN E4111: Big Data in Transportation
  • COMS W3203: Discrete Math
  • ECON W4280: Corporate Finance 
  • ECON W4860: Behaviorial Finance
  • MEIE E4810: Introduction to Humans in Space Flight
  • MECE E3018: Mechanical Engineering Laboratory
  • MECE E4608: Manufacturing Processes
  • STAT W4282: Linear Regression and Time Series Method

If there are other electives of interest, the student should bring the course description to his or her faculty advisor for review.