Electrical and Systems Engineering

Systems Engineering Program

MSE in SE Degree Requirements

Course Planning Guide (CPG)

Students must complete 10 Course Units in the following categories:

CATEGORY A: SE FOUNDATION5 Course Units

CATEGORY B: ESE ELECTIVE 1 Course Unit

CATEGORY C: TECHNICAL ELECTIVES 2 Course Units

CATEGORY D: APPLICATION AREA 2 Course Units

CATEGORY A: SE FOUNDATION

Five (5) course units are required withing the three areas below. Students must select at least one course unit within each of the three areas.

 

ESE 5140 Graph Neural Networks
ESE 5280 Estimation & Detection
ESE 5380 Machine Learning for Time-Series Data
ESE 5390 Hardware/Software Co-Design for Machine Learning (Note: This course requires CIS 2400 or a similar course as a prerequisite and may not be suitable for some students)
ESE 5420 Statistics for Data Science
ESE 5460 Deep Learning
ESE 6450 Deep Generative Models
ESE 6500 Learning in Robotics
CIS 5190 or 5200 Machine Learning

ESE 5000 Linear System Theory
ESE 5030 Simulation Modeling and Analysis
ESE 5070 Networks and Protocols
ESE 5310 Digital Signal Processing
ESE 6650 Datacenter Architecture
ENM 5310 Data-driven Modeling and Probabilistic Scientific Computing

ESE 5060 Intro to Optimization Theory
ESE 5050 Control Systems
ESE 5430 Human Systems Engineering
ESE 6050 Convex Optimization
ESE 6190 Model Predictive Control

CATEGORY B: ESE ELECTIVE

One (1) course unit from any 5000 or 6000 level ESE course.

CATEGORY C: TECHNICAL ELECTIVES

Two (2) course units from graduate-level offerings within: ESE, CIS, CIT*, IPD, MEAM, MSE, EAS**, or ENM

CATEGORY D: APPLICATION AREA

Two (2) course units from graduate-level offerings both from ONE of the Application Areas below.

None of these courses may duplicate topics studied in Categories A, B, or C.

If a course of interest is not listed in the Application Area, the student may send a completed petition (with relevant syllabus attached) to the Master’s Coordinator at least a week before Course Selection Period ends.

Petition

Energy & Environment
BEPP 7640 Climate and Financial Markets
EAS 5010 Energy and its Impacts: Technology, Environment, Economics, Sustainability
EAS 5020 Renewable Energy and Its Impacts: Technology, Environment, Economics, Sustainability
EAS 5030 Energy Systems and Policy
EAS 5050 Climate Policy and Technology
ENMG 5070 Effective Policy for the Energy Transition
ESE 5670 (BEPP/OIDD 7610) Risk Analysis and Environmental Management
FNCE 7560 Finance Energy
OIDD 5250 Thinking with Models: Business Analytics for Energy and Sustainability
OIDD 7630 (BEPP7630) Energy Markets & Policy
MSE 7900 Energy, Water, and Materials for the AI Economy
EAS Entrepreneurship
EAS 5120 Engineering Negotiation
EAS 5410 Engineering Entrepreneurship Fellows I
EAS 5430 Engineering Entrepreneurship Fellows II
EAS 5450/IPD5450 Engineering Entrepreneurship I
EAS 5460 Engineering Entrepreneurship II
EAS 5470 Engineering Project Management from Theory to Practice
EAS 5490 Engineering Entrepreneurship Lab
EAS 5950 Foundations of Leadership
Transportation & Logistics
ESE 5480/CPLN 6500 Transportation Planning Methods
ESE 5500/CPLN 7500 Advanced Transportation Seminar
MKTG 7250 Principles of Retailing
OIDD 6110  Quality and Productivity
OIDD 6120 Business Analytics
OIDD 6320 Operations Management: Supply Chain Management
OIDD 6420  Analytics for Services
OIDD 6590 Advanced Topics—Choice Architecture Lab
OIDD 6800 Operations Strategy Practicum
Human Factors/IPD
EAS 5470 Engineering Project Management from Theory to Practice
IPD 5090 Needfinding
IPD 5140/5150 Design
IPD 5720 Design Thinking
Robotics
NOTE: Probably need a BS‐EE to satisfy prerequisites of some courses.
MEAM 5100 Design of Mechatronic Systems
MEAM 5200 Intro to Robotics
MEAM 6240 Distributed Robotics
ESE 6250 Nanorobotics
ESE 6500 Learning in Robotics
MEAM 6200  Robotics
CIS 5800 Machine Perception
CIS 5810 Computer Vision & Computational Photography
CIS 6800 Advanced Topics in Machine Perception
CIT 5900 Programming Languages and Techniques
Embedded Systems/Internet of Things (IoT)
NOTE: Probably need a BS‐EE to satisfy prerequisites of some courses.
CIS 5400  Principles of Embedded Computation
CIS 5410 Embedded Software for Life‐critical Applications
CIS 5500 Database and Information Systems
CIS 5550 Internet and Web Systems
CIT 5900 Programming Languages and Techniques
ESE 5180 IoT Wireless, Security, & Scaling
ESE 5190 Smart Devices (previously titled “Real‐Time and Embedded Systems”)
ESE 5160 IoT Edge Computing
Bio‐Engineering/Medicine
BE 5020 From Biomedical Science to the Marketplace.
BE 5040 Biological Data Science II: Data Mining Principles for Epigenomics
BE 5460 Fundamental Techniques of Imaging I
BE 5470 Fundamental Techniques of Imaging
BE 5670 Mathematical Computation Methods for Modeling Biological Systems (this version only)
ESE 5660 Networked Neuroscience
MATH 5840/BE 5840 The Mathematics of Medical Imaging and Measurement
MATH 585 The Mathematics of Medical Imaging and Measurement
Health Care
HCMG 8410 Health Services System
HCMG 8530 Medical Devices
HCMG 8570 Healthcare Data and Analytics
HCMG 8660 E‐Health: Business Models and Impact
HCMG 8670 Health Care Entrepreneurship
HCMG 8700 The Business of Behavioral Health
HCMG 8900 Advanced Study Project: Management of Health Care Service Businesses
OIDD 6650  Operations Management in Health Care
STAT
STAT 5010 Introduction to Nonparametric Methods and Log-linear Models
STAT 5020 (EDUC683) Survey Methods and Design
STAT 5200  Applied Econometrics I
STAT 5210 Applied Econometrics II
STAT 5330 Stochastic Processes
STAT 5440 Applied Bayesian Modeling
STAT 5710 Modern Data Mining
STAT 5810 Convex Optimization for Statistics and Data Science
STAT 7110/5350 Forecasting Methods for Management (can ***NOT*** be “Campus: Online”)
STAT 7240 Text Analytics
STAT 9270 Bayesian Statistical Theory and Methods
STAT 9710 Introduction to Linear Statistical Models
ESE 6740 Information Technology
MKTG 7120 Data and Analysis for Marketing Decisions
MKTG 7520 Marketing Analytics
MKTG 7760 Applied Probability Models in Marketing
MKTG 8090 Experiments for Business Decision Making
EDUC 7847 Social & Statistical Network Analysis (SSNA)
Revenue Management
BEPP 8050 Risk Management
FNCE 7170 Financial Derivatives
OIDD 6120 Business Analytics
OIDD 6430 Analytics for Revenue Management
OIDD 676 Electronic Markets: Structures, Market Mechanisms and IT Enabled Strategies
MKTG 6110 Marketing Management
MKTG 6120 Dynamic Marketing Strategy
MKTG 6130 Strategic Marketing Simulation
MKTG 7120 Data and Analysis for Marketing Decisions
MKTG 7710 Models for Marketing Strategy
MKTG 7750 Managing Customer Value
MKTG 7760 Applied Probability Models in Marketing
ACCT
ACCT 6110 Fundamentals of Financial Accounting
ACCT 6130 Fundamentals of Financial and Managerial Accounting
ACCT 7060 Cost Management
ACCT 7470 Financial Statement and Disclosure Analysis
OIDD 6110 Quality and Productivity
OIDD 6730 Global Supply Chain Mgmt
Finance
FNCE 6110 Corporate Finance
FNCE 7050 Investment Management
FNCE 7070 Valuation
FNCE 7170 Financial Derivatives
FNCE 7250 Fixed Income Securities
FNCE 7370 Data Science for Finance
FNCE 7390 Behavioral Finance
FNCE 7500 Venture Capital and the Finance of Innovation
LGST 6440 Blockchain and Cryptocurrencies: Business, Legal and Regulatory Considerations

IMPORTANT NOTES:

*CIT Course Eligibility Maximum of two (2) CIT course units are allowed towards the degree

**EAS Course Eligibility Only the following EAS courses are permitted: EAS 5070, EAS 5100, EAS 5120, EAS 5450, EAS 5460, EAS 5470, EAS 5490, and EAS 5950.

ENM 5030: A course in Probability Theory is a prerequisite to CAT A courses. If you haven’t already satisfied this, it is necessary to take ENM 5030: Probability as your Category C technical elective in the first semester.

ESE 6800 Special Topics This course can be taken several times and counted more than once toward the degree. Each ESE 6800 course taken must address a different topic to be eligible. Student must seek Category approval for ESE 6800 by sending a completed petition (with ESE 6800 syllabus attached) to the Master’s Coordinator at least a week before Course Selection Period ends.

ESE 9990 Master’s Thesis Option ESE 9990 may count toward Category D ESE 5970 Master’s Thesis Research (2 course units).

ESE 5990 Independent Study Maximum of one (1) course unit can be used toward the degree and may count toward Category C only. Requires program approval.

Cross-Listed Courses

  1. For a cross-listed course, you will receive credit for enrolling in the ESE version only (no other sections may be counted, even if previously taken). This is not petitionable.
  2. Courses numbered 5000 or above are graduate-level courses. Master’s students must be registered for the graduate section to obtain credit toward the master’s curriculum. Undergraduate-level numbers will not be counted toward this degree. This is not petitionable.
  3. Grad/Undergrad cross-listed courses whose Undergrad section is below 4000 will not be approved.
  4. Students may use up to 2 cross-listed courses whose Grad and Undergrad sections are equivalent. Student must obtain approval by sending the syllabus to the Graduate Coordinator at least a week before Course Selection Period ends.

Transfer Courses Maximum of two (2) graduate-level course units may be transferred from another school to apply towards the degree. These cannot have been used to fulfill undergraduate degree requirements.

Transfer Courses