MSE in EE Degree Requirements
Course Planning Guide (CPG)
Students must complete 10 Course Units in the following categories:
CATEGORY A: EE CORE 5 Course Units
CATEGORY B: ESE ELECTIVES 2 Course Units
CATEGORY C: SEAS ELECTIVES 1 Course Unit
CATEGORY D: OPEN ELECTIVES 2 Course Units
CATEGORY A: EE CORE
- Five (5) course units are required in any of the areas below.
- Students can select any combination from within these areas and are not limited to a single area.
Physical Devices & Nano Systems
| ESE 5090: Quantum Circuits and Systems |
| ESE 5100: Electromagnetic & Optical Theory |
| ESE 5130: Prin of Quantum Tech |
| ESE 5210: The Physics of Solid State Energy Devices |
| ESE 5230: Quantum Engineering |
| ESE 5250: Nanoscale Science and Engineering |
| ESE 5290: Introduction to MEMS and NEMS |
| ESE 5360: Nanofabrication and Nanocharacterization |
Circuits & Computer Engineering
| ESE 5150: Internet of Things Sensors and Systems |
| ESE 5160: IoT Edge Computing |
| ESE 5190: Smart Devices (previously titled “Introduction to Embedded Systems”) |
| ESE 5320: System-On-A-Chip Architecture |
| ESE 5350: Electronic Design Automation |
| ESE 5390: HW/SW Co-Design for ML |
| ESE 5700: Digital Integrated Circuits & VLSI Fundamentals |
| ESE 5720: Analog Integrated Circuits |
| ESE 5780: RFIC (Radio Frequency Integrated Circuit) Design |
| ESE 5800: Power Electronics |
| ESE 6680: Mixed Signal Design and Modeling |
Information & Decision Systems
| ESE 5000: Linear Systems Theory |
| ESE 5030: Simulation Modeling and Analysis |
| ESE 5050: Feedback Control Design and Analysis |
| ESE 5060: Intro to Optimization Theory (previously “ESE 5040: Intro to Linear, Nonlinear, and Integer Optimization”) |
| ESE 5070: Introduction to Networks and Protocols |
| ESE 5120: Dynamical Systems for Engineering and Biological Applications |
| ESE 5140: Graph Neural Networks |
| ESE 5280: Estimation and Detection Theory |
| ESE 5300: Elements of Probability Theory |
| ESE 5310: Digital Signal Processing |
| ESE 5420: Statistics for Data Science |
| ESE 5450: Data Mining: Learning from Massive Datasets |
| ESE 5460: Principles of Deep Learning |
CATEGORY B: ESE ELECTIVES
- Two (2) course units from any graduate-level ESE course.
CATEGORY D: OPEN ELECTIVES
- Two (2) course units of approved electives from graduate courses at Penn in SEAS, SAS, Medicine, Law, Wharton MBA, Social Policy, and Education.
- Open Elective courses must have technical/scientific content and relevance to the student’s program.
- Approval must be obtained from the ESE department via petition prior to enrollment in the course.
- Pre-Approved courses that do not require a petition for Category D:
- Any course that could count in Category A, B, or C (per the above guidelines.)
- Any course listed as approved on the EE CPG Precedent List.
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 5950.
***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.
ESE 5970 Master’s Thesis Option If a thesis is completed, it will count for 1 or 2 course units of ESE 5970 toward the degree.
ESE 5990 Independent Study Maximum of one (1) course unit can be used toward the degree within a pre-approved category.
Cross-Listed Courses MUST be registered with the 5000-level course number to be eligible as a graduate level course. Any cross-listed section at the 4000-level or below is ineligible towards the degree.
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.