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Industrial and Systems Engineering (ISE)
- https://ise.usc.edu
- D class assignments available; URL: https://ise.usc.edu/current-students/.
- D class assignments for undergraduates available in GER-247; Phone: (213) 740-4893.
- D class assignments for undergraduates and on-campus graduate students available online or by phone call.
Methods, processes and tools for managing projects to create engineered systems. Project management; engineering economics; risk management. Industry-drawn large-scale engineering case studies. Team project presentations.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31515R | 902 | Lecture | 10:00-2:10pm | Tue, Thu | 1 of 40 | Yalda Khashe | OHE100B |   | |
| 31715D | 910 | Lecture | 10:00-2:10pm | Tue, Thu | 20 of 20 | Yalda Khashe | DEN@Viterbi | |
Supervised learning. Linear regression, cross validation, ridge and lasso regression, logistic regression, k-nearest-neighbors, decision trees, random forest and gradient-boosting models, support vector machines, neural networks.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31529R | 901 | Lecture | 2:00-5:10pm | Tue, Thu | 7 of 30 | Tao Ma | OHE120 | PDF (270312 KB) | |
| 31746D | 909 | Lecture | 2:00-5:10pm | Tue, Thu | 2 of 20 | Tao Ma | DEN@Viterbi | |
Methods and algorithms for automated text analysis; machine learning; predictive web data analytics; information retrieval; social media data; natural language documents and graphs.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31798D | 909 | Lecture | 12:00-3:10pm | Tue, Thu | 0 of 20 | Maryam Pishgar | DEN@Viterbi | | |
| 31799R | 901 | Lecture | 12:00-3:10pm | Tue, Thu | 7 of 40 | Maryam Pishgar | KAP158 | |
Explores fundamental techniques such as recursion, Fourier transform ordering, dynamic programming for efficient algorithm construction. Examples include arithmetic, algebraic, graph, pattern matching, sorting, searching algorithms.
- Crosslist: This course is offered by the CSCI department but may qualify for major credit in ISE. To register, enroll in CSCI 570.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 29928R | 527 | Lecture | 3:00-6:10pm | Mon, Wed | 43 of 210 | Shahriar Shamsian | SGM124 | | |
| 29929R | 527 | Discussion | TBA | TBA | 43 of 210 | OFFICE | | ||
| 29930R | 527 | Quiz | TBA | TBA | 43 of 210 | OFFICE | | ||
| 29931D | 952 | Lecture | 3:00-6:10pm | Mon, Wed | 10 of 30 | Shahriar Shamsian | DEN@Viterbi | | |
| 29932R | 952 | Discussion | TBA | TBA | 10 of 30 | DEN@Viterbi | | ||
| 29933R | 952 | Quiz | TBA | TBA | 10 of 30 | DEN@Viterbi | |
Economic evaluations of engineering systems for both government and private industry; quantitative techniques for evaluating non-monetary consequences; formal treatment of risk and uncertainty.
- Prerequisite: ISE 500
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31561R | 901 | Lecture | 12:00-3:10pm | Mon, Wed | 1 of 30 | Shalini Gupta | OHE122 | | |
| 31761D | 909 | Lecture | 12:00-3:10pm | Mon, Wed | 5 of 10 | Shalini Gupta | DEN@Viterbi | |
Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.
- Crosslist: This course is offered by the CSCI department but may qualify for major credit in ISE. To register, enroll in CSCI 567.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 29922R | 901 | Lecture | 11:00-1:05pm | MTuWTh | 16 of 80 | Victor Adamchik | OHE132 | PDF (177213 KB) | |
| 29923R | 901 | Discussion | TBA | TBA | 16 of 80 | OFFICE | | ||
| 29924R | 901 | Quiz | TBA | TBA | 16 of 80 | OFFICE | | ||
| 29925D | 909 | Lecture | 11:00-1:05pm | MTuWTh | 4 of 30 | Victor Adamchik | DEN@Viterbi | PDF (177213 KB) | |
| 29926R | 909 | Discussion | TBA | TBA | 4 of 30 | DEN@Viterbi | | ||
| 29927R | 909 | Quiz | TBA | TBA | 4 of 30 | DEN@Viterbi | |
The role enterprise resource planning systems (ERPs) play in organization; integrating and coordinating the many business processes such as demand planning, procurement, production and sales.
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31583R | 901 | Lecture | 10:00-11:50am | MWF | 4 of 30 | Nitin Kale | OHE100D | Word (295424 KB) | |
| 31783D | 909 | Lecture | 10:00-11:50am | MWF | 13 of 15 | Nitin Kale | DEN@Viterbi | |
Research leading to the doctorate. Maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.
| Section | Session | Units | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|---|
| 31790D | 908 | 1.0-6.0 | Lecture | TBA | TBA | 0 of 15 | Maged Dessouky | OFFICE | |
Credit on acceptance of Dissertation.
- Restriction: Registration open to the following class level(s): Doctoral Student
| Section | Session | Type | Time | Days | Registered | Instructor | Location | Syllabus | Info |
|---|---|---|---|---|---|---|---|---|---|
| 31791D | 908 | Lecture | TBA | TBA | 0 of 5 | OFFICE | |