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Operations Research Curriculum

The operations research curriculum helps students see their path through the three semesters of the MOR or MSOR degree.

Last Updated: 02/18/2026 | All information is accurate and still up-to-date

This guide helps you, the operations research student, plan your three semesters for your MOR or MSOR degree. Therefore, use this template flexibly to fit your schedule. Additionally, regularly talk with your advisor about your progress. Furthermore, check the course directory for prerequisites before registering for classes.

This guide helps you understand your courses and what they involve. Moreover, each course has a + link that includes:

  • The course description
  • Its credit hours

Master of Operations Research Curriculum (MOR)

Red = Core Course, Blue = Elective

OR PRO TIP: Use this template flexibly to fit your schedule. Additionally, regularly talk with your advisor about your progress. Furthermore, check the course directory for prerequisites before registering for classes.

Semester 1

OR 601  Seminar in Operations Research

  • You will discuss operations research problems in seminars. Additionally, you will analyze cases and write reports. If you are a graduate student with a minor or major in operations research, you must attend throughout your residence.
  • Hours: 1

Core Class

Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
MA 540 Uncertainty Quantification
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

Core Class

Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
MA 540 Uncertainty Quantification
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Total Hours: 10

Semester 2

Core Class

Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
MA 540 Uncertainty Quantification
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Total Hours: 12

Semester 3

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Total Hours: 9

Minimum Credit Hours Required for Graduation: 31

Master of Science in Operations Research Curriculum (MSOR)

A diagram showing each semester and the OR courses a student will take. Semester 1 is OR 601, two core classes and an elective. Semester 2 is one core class, two electives and your thesis. Semester three is two electives and your thesis. The details for each course are listed below.
Red = Core Course, Blue = Elective, Green = Thesis

OR PRO TIP: This guide is a template and doesn’t have to be followed exactly. The MOR and MSOR are highly flexible, so you can move courses around to fit your schedule. Talk with your advisor regularly about your progress.

Semester 1

OR 601  Seminar in Operations Research

  • You will discuss operations research problems in seminars. Additionally, you will analyze cases and write reports. If you are a graduate student with a minor or major in operations research, you must attend throughout your residence.
  • Hours: 1

Core Class

Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
MA 540 Uncertainty Quantification
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

Core Class

Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
MA 540 Uncertainty Quantification
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Total Hours: 10

Semester 2

Core Class

Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
MA 540 Uncertainty Quantification
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Thesis (OR 695 Master’s Thesis Research)

  • First, you must complete a master’s thesis, typically involving 3 to 6 credits of OR 695 Master’s Thesis Research. Ideally, your thesis should include publishable research.
  • Next, form a Graduate Advisory Committee with at least three faculty members and file a committee-approved Plan of Graduate Work with the Graduate School. Ensure your Chair (or co-chair) and one other member are from the OR Faculty. Additionally, include one member as the Graduate School Representative and one representing your minor field of study.
  • Finally, pass your final oral examination conducted by your Advisory Committee. This exam will include, but is not limited to, a “defense of thesis.”
  • Once you pass the MSOR final oral examination, ensure that each committee member approves your thesis. Submit the thesis to the thesis editor of the Graduate School, adhering to the Guide for Preparation of Theses and Dissertations available from the Graduate School. For detailed information about ETDs, refer to the Electronic Theses and Dissertations page.
  • .OR PRO TIP: Be aware of Graduate School submission deadlines for graduation.
  • Hours: 3

Total Hours: 12

Semester 3

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Elective

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Thesis (OR 695 Master’s Thesis Research)

  • First, you must complete a master’s thesis, typically involving 3 to 6 credits of OR 695 Master’s Thesis Research. Ideally, your thesis should include publishable research.
  • Next, form a Graduate Advisory Committee with at least three faculty members and file a committee-approved Plan of Graduate Work with the Graduate School. Ensure your Chair (or co-chair) and one other member are from the OR Faculty. Additionally, include one member as the Graduate School Representative and one representing your minor field of study.
  • Finally, pass your final oral examination conducted by your Advisory Committee. This exam will include, but is not limited to, a “defense of thesis.”
  • Once you pass the MSOR final oral examination, ensure that each committee member approves your thesis. Submit the thesis to the thesis editor of the Graduate School, adhering to the Guide for Preparation of Theses and Dissertations available from the Graduate School. For detailed information about ETDs, refer to the Electronic Theses and Dissertations page.
  • .OR PRO TIP: Be aware of Graduate School submission deadlines for graduation.
  • Hours: 3

Total Hours: 9

Minimum Credit Hours Required for Graduation: 31