Electrical and Systems Engineering
A Department of the School of Engineering and Applied Science
MSE in SE Degree Requirements
Course Planning Guide (CPG)
Students must complete 10 Course Units in the following categories:
CATEGORY A: SE FOUNDATION 5 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 within the three areas below.
- Students must select at least one course unit within each of the three areas.
Data Science
| 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 Machine Learning |
| ESE 5460 Deep Learning |
| ESE 6450 Deep Generative Models |
| ESE 6500 Learning in Robotics |
| CIS 5190 or 5200 Machine Learning |
System Modeling
| 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 |
Systems Design & Optimization
| 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 D: APPLICATION AREA
- Two (2) course units from graduate-level offerings 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.
Application Areas
| 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 |
| 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
- 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.
- 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.
- Grad/Undergrad cross-listed courses whose Undergrad section is below 4000 will not be approved.
- 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.