The management science and systems discipline in the Management PhD program prepares students to become leading researchers and teachers at top universities or executive-level decision makers in industry. Each student follows a slightly different path, depending on research interests, allowing some flexibility to the curriculum.
You must develop or have competence in accounting, economics, finance, marketing, organizational behavior/organizational theory and strategic management equivalent to one first-year MBA course in each area before graduating from the PhD program.
ECON 613** Introduction to Econometrics
ECON 614** Econometric Applications and Methods
IE 576** Applied Stochastic Processes
MGQ 614 Advanced Probability and Statistics or IE575
MGQ 616 Stochastic Models of Management Science or IE 572
Credits: 3.00
Semesters offered:
MGS 786 Design Science
Credits: variable
Semesters offered: Fall 2020 | Spring 2021
Fall 2020 (08/31/2020 - 12/11/2020)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11981 | F4Q | TUT | ARR | Arr Arr | Unknown | ||
| 11994 | F2Q | TUT | ARR | Arr Arr | Unknown | ||
| 12064 | F1Q | TUT | ARR | Arr Arr | Unknown | ||
| 11910 | F3Q | TUT | ARR | Arr Arr | Unknown |
Spring 2021 (02/01/2021 - 05/07/2021)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11078 | S4Q | TUT | ARR | Arr Arr | Unknown | ||
| 11262 | S1Q | TUT | ARR | Arr Arr | Unknown | ||
| 11161 | S3Q | TUT | ARR | Arr Arr | Unknown | ||
| 11226 | S2Q | TUT | ARR | Arr Arr | Unknown |
(Fall: must register for two consecutive years)
Credits: variable
Semesters offered: Fall 2020 | Spring 2021
Fall 2020 (08/31/2020 - 12/11/2020)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11852 | F5S | TUT | ARR | Arr Arr | Ramesh, Ramaswamy | ||
| 11932 | F7S | TUT | ARR | Arr Arr | Smith, Sanjukta Das | ||
| 12055 | F4S | TUT | ARR | Arr Arr | Sharman, Raj | ||
| 11873 | F6S | TUT | ARR | Arr Arr | Unknown | ||
| 11996 | F3S | TUT | ARR | Arr Arr | Unknown | ||
| 11908 | F2S | TUT | ARR | Arr Arr | Unknown | ||
| 12050 | F1S | TUT | ARR | Arr Arr | Sanders, George L. |
Spring 2021 (02/01/2021 - 05/07/2021)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11230 | S2S | TUT | ARR | Arr Arr | Smith, Sanjukta Das | ||
| 11116 | S6S | TUT | ARR | Arr Arr | Sharman, Raj | ||
| 11099 | S5S | TUT | ARR | Arr Arr | Ramesh, Ramaswamy | ||
| 11162 | S3S | TUT | ARR | Arr Arr | Unknown | ||
| 11126 | S8S | TUT | ARR | Arr Arr | Unknown | ||
| 11120 | S7S | TUT | ARR | Arr Arr | Sanders, George L. | ||
| 11268 | S1S | TUT | ARR | Arr Arr | Suresh, Nallan Chakravarthy |
(Spring: must register for two consecutive years)
This course teaches the technical and managerial skills needed in developing predictive analytics applications which are used by customer-centric corporations - retail, financial, communication, and marketing groups - to help make decisions involving complex systems. The course concentrates on a set of well-known predictive analytics methods to support business decision making. Topics such as association rule mining, decision trees, neural networks, regression analysis and cluster analysis are covered in great depth. Extensive hands-on experience using software such as SAS Enterprise Miner is provided.
Credits: 3.00
Semesters offered: Fall 2020 | Spring 2021
Fall 2020 (08/31/2020 - 12/11/2020)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 21333 | F1S | LEC | TR | 9:35 - 10:50 a.m. | Nsc 201 | Smith, Sanjukta Das |
Spring 2021 (02/01/2021 - 05/07/2021)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 18623 | S3S | LEC | W | 11:30 a.m. - 12:50 p.m. | Nsc 201 | Smith, Sanjukta Das | |
| 24297 | S3SA | LEC | W | 11:30 a.m. - 12:50 p.m. | Remote | Smith, Sanjukta Das |
IE 573 Discrete Optimization
IE 575 Stochastic Methods
IE 551 Simulation and Stochastic Models
IE 675 Game Theory
This is an interdisciplinary course in Information Assurance that has two primary objectives: 1) to introduce students to fundamental concepts, terminologies, IA models and practices. 2) to view how different fields of disciplines interact in this area. The course will familiarize students with the technical, legal, socio-political, and managerial issues of IA. Broadly, the issues that we will cover in this course include: security investigation and analysis; ethical, legal, and professional aspects of Information assurance; risk management and implementation and maintenance of information assurance.
Credits: 3.00
Semesters offered: Fall 2020
Pre-Requisite: MGS 602.
Fall 2020 (08/31/2020 - 12/11/2020)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 18314 | F2S | LEC | TR | 5:30 - 6:45 p.m. | Talbrt 107 | Cleary, Kevin Patrick |
The main objective of this course is to introduce students to the theory and practice of doing business via the Internet. Topics include: elements of the infrastructure of electronic commerce; technologies and applications in electronic commerce; using electronic commerce for the creation of competitive advantages; planning technology-based strategies to achieve business goals. The course will rely heavily on research and peer learning with the instructor serving as catalyst, facilitator, and evaluator in a collaborative environment.
Credits: 3.00
Semesters offered: Spring 2021
Spring 2021 (02/01/2021 - 05/07/2021)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11275 | S1S | LEC | R | 7:05 - 9:45 p.m. | Knox 109 | Miles, Stephen |
** Courses satisfying statistics and methodology requirements.
If you are a doctoral student outside of the School of Management who is interested in obtaining an external area of focus in Management Science and Systems, you should consult with your academic advisor. Course requirements are:
Refer to the PhD Handbook for complete information on:
