The master's degree program in electrical and computer engineering offers in-depth coursework within the concentration-choice-related areas. The curriculum is integrated and intensive and is built on state-of-the-art research, taught by faculty who are experts in their areas.
Excluded Courses for All MSECE Concentrations
Students cannot take excluded courses as part of the MSECE program and may not petition to take these courses, as any petition to take these courses will be automatically rejected. Courses from the following subject areas may not count toward any concentration within the MSECE program: CSYE, ENSY, EMGT, INFO, SBSY, TELE. Select CS courses are also excluded from all MSECE concentrations. Please see the Program Requirements tab and your college administrator for more information.
Graduate Certificate Options
Students enrolled in a master's degree have the opportunity to also pursue one of the many engineering graduate certificate options in addition to or in combination with the MS degree. Students should consult their faculty advisor regarding these options.
Gordon Institute of Engineering Leadership
Master's Degree in Electrical and Computer Engineering with Concentration in Hardware and Software for Machine Intelligence with Graduate Certificate in Engineering Leadership
Students may complete a Master of Science in Electrical and Computer Engineering with Concentration in Hardware and Software for Machine Intelligence in addition to earning a Graduate Certificate in Engineering Leadership. Students must apply and be admitted to the Gordon Engineering Leadership Program in order to pursue this option. The program requires fulfillment of the 16-semester-hour curriculum required to earn the Graduate Certificate in Engineering Leadership, which includes an industry-based challenge project with multiple mentors. The integrated 40-semester-hour degree and certificate will require 24 semester hours of advisor-approved hardware and software for machine intelligence technical courses.
Complete all courses and requirements listed below unless otherwise indicated.
Fundamental Courses
Code | Title | Hours |
---|---|---|
Complete at least 8 semester hours from the following: | 8 | |
Introduction to Machine Learning and Pattern Recognition | ||
Fundamentals of Computer Engineering | ||
Computer Architecture | ||
VLSI Design |
Options
Complete one of the following options:
Coursework Option
Code | Title | Hours |
---|---|---|
A maximum of three courses may be taken outside of the electrical and computer engineering EECE subject code. | ||
Depth Courses | ||
Complete 12 semester hours from the depth course list below. Any fundamental course not used to meet the fundamental course requirement can be used toward the depth course requirement. | 12 | |
Breadth Courses | ||
Complete 8 semester hours from the breadth course list below or other EECE courses chosen in consultation with a faculty advisor. | 8 | |
Note: Depth courses cannot be taken for breadth. | ||
Elective | ||
Complete 4 semester hours of either depth or breadth courses. | 4 |
Thesis Option
Code | Title | Hours |
---|---|---|
A maximum of three courses may be taken outside of electrical and computer engineering. | ||
Thesis | ||
EECE 7990 | Thesis | 8 |
Depth Courses | ||
Complete 4 semester hours from the depth course list below. | 4 | |
Breadth Courses | ||
Complete 4 semester hours from the breadth course list below or other EECE courses chosen in consultation with a faculty advisor. | 4 | |
Note: Depth courses cannot be taken for breadth. | ||
Elective | ||
Complete 8 additional semester hours from either depth or breadth courses. | 8 |
Course Lists
Depth Courses
Code | Title | Hours |
---|---|---|
Foundations of Artificial Intelligence | ||
Reinforcement Learning and Sequential Decision Making | ||
Robotic Science and Systems | ||
Theory and Methods in Human Computer Interaction | ||
Mobile Robotics | ||
Assistive Robotics | ||
Robotics Sensing and Navigation | ||
Statistical Inference: An Introduction for Engineers and Data Analysts | ||
Computer Vision | ||
High-Performance Computing | ||
Introduction to Software Security | ||
Data Visualization | ||
Simulation and Performance Evaluation | ||
Introduction to Machine Learning and Pattern Recognition | ||
Parallel Processing for Data Analytics | ||
Special Topics in Electrical and Computer Engineering (Reinforcement Learning) | ||
Computer Hardware and System Security | ||
Autonomous Field Robotics | ||
Applied Probability and Stochastic Processes | ||
Fundamentals of Computer Engineering | ||
Introduction to Distributed Intelligence | ||
Numerical Optimization Methods | ||
Information Theory | ||
Big Data and Sparsity in Control, Machine Learning, and Optimization | ||
Probabilistic System Modeling and Analysis | ||
Computer Architecture | ||
VLSI Design | ||
High-Level Design of Hardware-Software Systems | ||
Advanced Computer Vision | ||
Computer Hardware Security | ||
Analysis and Design of Data Networks | ||
Advanced Machine Learning | ||
Advanced Special Topics in Electrical and Computer Engineering (Legged Robotics) | ||
Advanced Special Topics in Electrical and Computer Engineering (Human Centered Computing) | ||
Advanced Special Topics in Electrical and Computer Engineering (Advances in Deep Learning) | ||
Advanced Special Topics in Electrical and Computer Engineering (Deep Learning Embedded Systems) | ||
Advanced Special Topics in Electrical and Computer Engineering (Security in Large-Scale Learning-Enabled Systems) | ||
Preparing High-Stakes Written and Oral Materials (Only for PhD and MS Thesis students) | ||
Special Problems in Electrical and Computer Engineering | ||
Master’s Project (MS Thesis students cannot take this course) | ||
Neural Networks and Deep Learning | ||
Graph Theory | ||
AI Ethics |
Breadth Courses
Code | Title | Hours |
---|---|---|
Database Management Systems | ||
Computer Systems | ||
Compilers | ||
Advanced Software Development | ||
Privacy, Security, and Usability | ||
Software Vulnerabilities and Security | ||
Network Security | ||
Wireless Sensor Networks and the Internet of Things | ||
Dynamical Systems in Biological Engineering | ||
Thin Film Technologies | ||
Introduction to Multiferroics Materials and Systems | ||
Combinatorial Optimization | ||
Wireless Communication Systems | ||
Classical Control Systems | ||
Micro- and Nanofabrication | ||
Digital Control Systems | ||
Image Processing and Pattern Recognition | ||
Nanophotonics | ||
Design of Analog Integrated Circuits with Complementary Metal-Oxide-Semiconductor Technology | ||
Microwave Circuits and Systems | ||
Signal Processing for Global Navigation Satellite Systems | ||
Digital Signal Processing | ||
Sustainable Energy: Materials, Conversion, Storage, and Usage | ||
Electric Drives and Lab for EECE 5680 | ||
Power Systems Analysis 1 | ||
Power Electronics and Lab for EECE 5684 | ||
Analysis of Unbalanced Power Grids | ||
Electromagnetic Devices for RF and Wireless Communications | ||
Acoustics and Sensing | ||
Special Topics in Electrical and Computer Engineering (Introduction to Quantum Engineering) | ||
Special Topics in Electrical and Computer Engineering (Network Programming) | ||
Special Topics in Electrical and Computer Engineering (Biomedical Microsystems) | ||
Special Topics in Electrical and Computer Engineering (Design and Prototyping of Optical Systems for Engineering Applications) | ||
Special Topics in Electrical and Computer Engineering (Electric Vehicles) | ||
Special Topics in Electrical and Computer Engineering (Feedback Control Systems: Applications to Unmanned Aerial Vehicles) | ||
Special Topics in Electrical and Computer Engineering (GNSS Signal Processing) | ||
Special Topics in Electrical and Computer Engineering (Photonic Devices for Communication Systems) | ||
Special Topics in Electrical and Computer Engineering (Networks: Technology, Economics, Social Interactions) | ||
Special Topics in Electrical and Computer Engineering (Advanced Network Management) | ||
Special Topics in Electrical and Computer Engineering (Electromagnetic Devices) | ||
Special Topics in Electrical and Computer Engineering (Introduction to Organic and Printed Electronics) | ||
Optics for Engineers | ||
Linear Systems Analysis | ||
Solid State Devices | ||
Electromagnetic Theory 1 | ||
Complex Variable Theory and Differential Equations | ||
Nonlinear Control | ||
System Identification and Adaptive Control | ||
Optimal and Robust Control | ||
Power Systems State Estimation | ||
Modeling and Simulation of Power System Transients | ||
Advanced Power Electronics | ||
Analog Integrated Circuit Design and Lab for EECE 7240 | ||
Integrated Circuits for Mixed Signals and Data Communication | ||
Introduction to Microelectromechanical Systems (MEMS) | ||
Microwave Circuit Design for Wireless Communication | ||
Radio Frequency Integrated Circuit Design | ||
Power Management Integrated Circuits | ||
Electromagnetic Theory 2 | ||
Computational Methods in Electromagnetics | ||
Antennas and Radiation | ||
Optical Properties of Matter | ||
Modern Imaging | ||
Electronic Materials | ||
Advanced Magnetic Materials—Magnetic Devices | ||
Modern Signal Processing | ||
Digital Communications | ||
Mobile and Wireless Networking | ||
Fundamentals of Computer Networks | ||
Operating Systems: Interface and Implementation | ||
Advanced Special Topics in Electrical and Computer Engineering (Low Power Integrated Circuits Design) | ||
Advanced Special Topics in Electrical and Computer Engineering (Wireless Network Systems and Applications) | ||
Advanced Special Topics in Electrical and Computer Engineering (Advanced Computer Architecture) | ||
Advanced Special Topics in Electrical and Computer Engineering (Power System Constrained Optimization) | ||
Advanced Special Topics in Electrical and Computer Engineering (Advanced Radio Frequency Passive Technologies) | ||
Preparing High-Stakes Written and Oral Materials | ||
Advanced Control Engineering |
Excluded Courses for All MSECE Concentrations
Please see your college administrator for more information.
Code | Title | Hours |
---|---|---|
Courses from the following subject areas may not count toward any concentration within the MSECE program: | ||
CSYE, ENSY, EMGT, INFO, SBSY, TELE | ||
The following CS courses may not count toward any concentration within the MSECE program: | ||
Programming Design Paradigm | ||
Pattern Recognition and Computer Vision | ||
Computer/Human Interaction | ||
Mobile Application Development | ||
Web Development | ||
Fundamentals of Computer Networking | ||
Algorithms | ||
Empirical Research Methods | ||
Wireless Network |
Program Credit/GPA Requirements
32 total semester hours required
Minimum 3.000 GPA required