BS Industrial Engineering Required & Core Courses

Below are the courses required to earn a bachelor's of science in industrial engineering from the College of Engineering at the University of South Florida. Information is based on the 2023-2024 Undergraduate Catalog.

Download PDF: Bachelor of Science in Industrial Engineering (BSIE) Prerequisite and Core Courses

Prerequisite courses to be completed prior to department admission

Course  Description
EGN 3443 - Probability and Statistics for Engineers An introduction to concepts of probability and statistical analysis with special emphasis on critical interpretation of data, comparing and contrasting claims, critical thinking, problem solving, and writing.
EGN 3615 - Engineering Economics w/Social & Global Implications Presents basic economic models used to evaluate engineering project investments with an understanding of the implications of human and cultural diversity on financial decisions through lectures, problem solving, and critical writing.
EGN 4450 - Introduction to Linear Systems Study and application of matrix algebra, differential equations and calculus of finite differences.
EGN 1113 - Intro to Design Graphics An introductory course covering the principles of technical drawing by employing traditional and Computer-Aided-Drafting (CAD) techniques using AutoCAD. Students will also learn to apply these concepts to civil design and engineering plans preparation.

Core Courses
Course Description
EIN 4621 - Manufacturing Processes The study of basic manufacturing processes and precision assembly. CAD/CAM including NC programming.
ESI 4312 - Foundations of Optimization This course covers basic techniques for modeling and optimizing deterministic systems with emphasis on linear programming, network optimization, basic mixed integer programming, and nonlinearprogramming. Students learn how to compute solutions of various optimization problems. Applications to production, logistics, and service systems are discussed.
EIN 4312C - Work Analysis  
ESI 4007 - Engineering Programming A problem based approach to describing programming concepts using Visual Basic for Applications and MS Excel.
EIN 4333 - Production Control Planning and control of production systems. Includes: forecasting and inventory control models, scheduling and sequencing, MRP, CPM/PERT, and resource requirements.
ESI 4221 - Statistical Methods in Quality Analytics This course will present data driven theory and methods of quality monitoring including process capability, control charts, acceptance sampling, quality engineering, and quality design.
ESI 4313 - Stochastic Systems Probabilistic models in Operations Research. Discrete and continuous time processes, queuing models, inventory models, simulation models, Markovian decision process and decision analysis.
ESI 4620 - Principals of Data Engineering This course introduces the fundamentals of database management systems. The basic concepts for the design, use, and implementation of database systems will be presented in this course.
ESI 4606 - Analytics I - Foundations of Data Science With the rapid advancement of sensing technology and information systems, massive amounts of data are being generated in various fields, ranging from engineering to applied science. There is an increasing need for data scientists and analysts who have skills and knowledge to analyze and interpret such data in order to extract patterns and gain insights for problem solving and decision making.
ESI 4244 - Design of Experiments Activity forecasting models and control. Design and use of inventory control models, both designs applicable to engineering analyses. Analysis of variance and regression.
ESI 4523 - Systems Simulation A study of the development and analysis of computer simulation models: Monte Carlo, time-slice, and next-event. Introduction to special purpose simulation languages.
EIN 4601C - Automation and Robotics Introduction to the practices and concepts of automation as applied to material handling, inventory storage, material transfer, industrial processes and quality control.
ESI 4607 - Engineering Analytics II Future-based projections are an integral part of our lives. We make these projections/decisions either with tangible data or with intuition and experience. Massive amounts of data are being generated in various fields, ranging from engineering to applied science. This course focuses on the practice of predictive and prescriptive analytics by developing models using statistical learning tools and quantifying their prediction accuracy on unseen data.