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 5730: Chips-design
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 5380: Machine Learning for Time-Series Data
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 C: SEAS ELECTIVE

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.
  • For courses cross-listed between ESE and another department: ONLY the ESE section may be eligible for Category A or Category B credit, following above guidelines. NO other department section may be counted toward Category A or Category B.

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.