Electrical Engineering - Master of Engineering in Electrical Engineering (Online)

Requirements and Options for the MEEE Degree

The Program Educational Objectives for the Master of Engineering Program in Electrical Engineering are:

  1. That graduates successfully apply advanced skills and techniques in one or more areas of emphasis.
  2. That graduates obtain relevant, productive employment with the private sector or in government and/or pursue additional advanced degrees.

The MEEE is a coursework-only option for obtaining a master's degree.  The requirement is a total of 30 credits of graduate course work, including passing with a grade of B or better six Graduate Expanded Core Courses from at least three different areas of emphasis.  No oral exam is required for the MEEE.

Prefix Title Credits
Graduate Expanded Core Courses: choose 6 from at least 3 different areas 118-21
Electromagnetic Theory I 23
Microwave Engineering3
Antennas and Radiation4
Introduction to Radar3
Smart Antennas3
Computational Electromagnetics3
Introduction to Analog and Digital VLSI3
ASIC Design3
Analog VLSI Design 23
ARM SOC Design3
Fundamentals of Photonics 24
Fourier Methods in Electro-Optics3
Optical System Design3
Electric Energy Systems
Electricity Markets3
Power System Operation3
Power System Relaying3
Power Electronics3
Photovoltaic Devices and Systems3
Power Systems II3
Power Systems III 23
Distribution Systems3
Digital Signal Processing
Digital Signal Processing II 23
Machine Learning I 33
Geometric Algebra 33
Deep Learning for Image Processing3
Advanced Image Processing3
Digital Image Processing 2,33
Neural Signal Processing3
Computer Engineering
Quantum Computing3
Hardware & Software Codesign3
Hardware Security and Trust3
Computer Systems Architecture 23
Computer Performance Analysis I3
Selected Topics (Applications of Parallel Computing XSEDE Collaborative Course)3
Mobile Application Development3
Random Signal Analysis 23
Modern Coding Theory3
Signal Compression3
Digital Communication Systems I3
Wireless Communications3
Information Theory3
Controls & Robotics
Control Systems Synthesis 23
Noncooperative Game Theory3
Machine Learning I 33
Geometric Algebra 33
Digital Image Processing 33
Graduate Electives: choose 3 to 4 courses 412-9
Total Credits30

The graduate expanded core courses must be passed with a grade of B or better.  Note--a grade of B- (or lower) in a graduate expanded core course will not satisfy completion of that course for the MEEE.


This course is one of the MSEE Graduate Core Courses.  Students pursuing the MEEE who wish to pursue the Ph.D. in the future are encouraged to select three courses from this subset of courses to satisfy one of the requirements for the Ph.D. Qualifying exam (see https://ece.nmsu.edu/grad-study/phd-qualifying.html) for more information.


This course is included in multiple areas of emphasis.  Students may use this course to satisfy one area of emphasis.


E E courses must be numbered 500 or higher.  Non-E E courses must be numbered 450 or higher.  Credits of E E 590 Selected Topics which are not subtitled are limited to a total of 6.

Other limitations and requirements that apply to all master’s degrees are described elsewhere in this catalog.

Included Prefixes

Graduate course work credits from the following prefixes are permitted for the MEEE degree.  If a graduate course outside this list of prefixes logically fits into the MEEE program, see your graduate advisor about requesting an exception.

Prefix Title Credits
College of Agriculture/Consumer/Environmental Sciences
College of Arts and Sciences
College of Business
College of Engineering

New Mexico State University master’s accelerated program provides the opportunity for academically qualified undergraduate students to begin working on a master’s degree during their junior and senior years while completing a bachelor’s degree. Typically, a bachelor’s degree requires four years to complete, and a master’s degree requires an additional two years. The master’s accelerated programs allow students the opportunity to complete a graduate program in an accelerated manner. Students can take up to 12 credits of E E graduate courses and get dual course credit that can be applied to both an undergraduate and master's degree.  You can also check NMSU’s catalog for additional information about our programs. 

MAP Requirements

  • The Graduate School allows qualified junior or senior students to substitute its graduate courses for required or elective courses in an undergraduate degree program and then subsequently count those same courses as fulfilling graduate requirements in a related graduate program.
  • Undergraduate students may apply for acceptance to the accelerated master’s program after completing 60 semester hours of undergraduate coursework of which a minimum of 25 semester credit hours must be completed at NMSU.
  • The grade point average must be at a minimum of 2.75.
  • Students must receive a grade of B or higher in this coursework to be counted for graduate credit. If a grade of B- or lower is earned, it will not count toward the graduate degree.

Accepted MAP Courses

The following courses are accepted for use in the MAP program.  Any other E E 500+ course that is taught concurrently with an E E 400+ course may be considered after a consultation with an advisor. An exception will need to be made to the degree audit in order for the additional course(s) to be included on both the Undergraduate and Graduate degrees. E E 450+ courses are not eligible for MAP credit nor are E E 500+ courses that are not taught concurrently with an E E 400+ course.  The following course list specifies which undergraduate BSEE concentration electives may count toward the MAP.  Courses are listed according to the most relevant BSEE concentration, but some courses may count toward multiple concentrations; please refer to the corresponding BSEE concentrations in the NMSU catalog for more details on concentration courses.

Prefix Title Credits
Artificial Intelligence, Machine Learning, & Data Science
E E 506Quantum Computing3
E E 565Machine Learning I3
Communications and Signal Processing
E E 573Signal Compression3
E E 581Digital Communication Systems I3
E E 588Advanced Image Processing3
E E 596Digital Image Processing3
E E 597Neural Signal Processing3
Computers and Microelectronics
E E 510Introduction to Analog and Digital VLSI3
E E 512ASIC Design3
E E 523Analog VLSI Design3
E E 556Hardware & Software Codesign3
E E 558Hardware Security and Trust3
E E 562Computer Systems Architecture3
E E 567ARM SOC Design3
E E 593Mobile Application Development3
Controls & Robotics
E E 551Control Systems Synthesis3
E E 576Geometric Algebra3
Electromagnetics and Photonics
E E 521Microwave Engineering3
E E 528Fundamentals of Photonics4
E E 541Antennas and Radiation4
E E 548Introduction to Radar3
E E 549Smart Antennas3
E E 502Electricity Markets3
E E 537Power Electronics3
E E 540Photovoltaic Devices and Systems3
E E 542Power Systems II3
E E 543Power Systems III3