Online Learning

Online Masters of Electrical Engineering (MS)

Mechanical engineering students in a lab.
The mean annual salary for electrical engineers is $99,580 with the top 10% earning $150,340 (US BLS). Boost your career with an online EE degree from an accredited university.

Cutting-Edge Communications and Signals Technology

Our electrical engineering program will help you master design and analysis skills to take on advanced electrical engineering and communications projects at the cutting-edge of technology. This distance-learning, research-based MS maintains the high standards of Michigan Tech graduate education.

#1 Best for power system engineers
OnlineMasters.com, 2019

#2 Public colleges where grads make six figures
Money Magazine, 2017

#6 Early career earnings
Money Magazine, 2017

#29 Online electrical engineering MS
OnlineMasters.com, 2019

Customize Your Online Education

Choose an electrical engineering focused area of study to get the most out of your accredited MS degree. Areas include:

  • Communication Theory
  • Signal Processing

Program Website

Curriculum

Focusing on the transmission, measurement, processing, analysis, and interpretation of all types of information-bearing signals, our electrical engineering program will prepare you to take the lead on more advanced electrical engineering projects, pursue new career opportunities, and succeed in supervisory roles. 10 courses can be completed in as few as five semesters.

Foundation Course

EE 5300 - Mathematical and Computational Methods in Engineering

Overview of problem-solving tools and techniques in engineering, considered from both the analytical and computational point of view. Systems of linear equations, eigenvalue and eigenvector computations, boundary value and initial value problems, Fourier analysis, large-scale systems, optimization. Mathematical modeling and computar programming.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall, Spring
  • Restrictions: Must be enrolled in one of the following Major(s): Electrical Engineering, Computer Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

Core 1 Courses

EE 5500 - Probability and Stochastic Processes

Theory of probability, random variables, and stochastic processes, with applications in electrical and computer engineering. Probability measure and probability spaces. Random variables, distributions, expectations. Random vectors and sequences. Stochastic processes, including Gaussian and Poisson processes. Stochastic processes in linear systems. Markov chains and related topics.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall, Spring
  • Restrictions: Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

EE 4252 - Digital Signal Processing and its Applications

Digital signal processing techniques with emphasis on applications. Includes sampling, the Z-transform, digital filters and discrete Fourier transforms. Emphasizes techniques for design and analysis of digital filters. Special topics may include the FFT, windowing techniques, quantization effects, physical limitations, image processing basics, image enhancement, image restoration and image coding.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall
  • Co-Requisite(s): EE 4259
  • Pre-Requisite(s): EE 3160

EE 4250 - Modern Communication Systems

Introduces the mathematical theory of communication science. Topics include baseband and digital signaling, bandpass signaling, AM and FM systems, bandpass digital systems, and case studies of communication systems.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall, Spring
  • Pre-Requisite(s): EE 3160 and (MA 3720 or EE 3180)

Core 2 Courses

EE 5900 - Special Topics in Electrical Engineering

Special topics in electrical engineering selected by the student and approved by his/her advisor and the faculty member who will approve the study.

  • Credits: variable to 5.0; May be repeated
  • Semesters Offered: Fall, Spring, Summer
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Computer Engineering

EE 5511 - Information Theory, Inference, and Learning Algorithms

Mathematical models for channels and sources; entropy, information, data compression, channel capacity, Shannon's theorems, and rate-distortion theory.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Spring - Offered alternate years beginning with the 2007-2008 academic year
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate
  • Pre-Requisite(s): EE 5500

EE 5521 - Detection & Estimation Theory

Detecting and estimating signals in the presence of noise. Optimal receiver design. Applications in communications, signal processing, and radar.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Spring
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Computer Engineering
  • Pre-Requisite(s): EE 5500

Communications Focus Area Courses

EE 5527 - Digital Communications

This course focuses on the basic principles that underlie the analysis and design of digital communication systems. Topics covered include: characterization of communication signals and systems, modulation schemes, optimum receiver design and performance analysis in AWGN and band-limited channels, concepts of information theory and channel coding, carrier and symbol synchronization, and ISI channel equalization.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Spring
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate
  • Pre-Requisite(s): EE 3250

EE 5525 - Wireless Communications

Principles of wireless communications systems. Projects may include cell phones, computer networks, paging systems, satellite communications, radio, television and telemetry.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate
  • Pre-Requisite(s): EE 5527

EE 5726 - Wireless Sensor Networks

Introduces the concepts of wireless sensor networks. Topics include sensor network coverage and sensor deployment, time synchronization and sensor node localization, network protocols, data storage and very, collaborative signal processing. Introduce sensor network programming network reliability and tolerance.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: On Demand
  • Pre-Requisite(s): (CS 4461 or EE 4272 or EE 5722) and (EE 3170 or EE 3173) and (CS 1129 or CS 2141)

Signal Processing Focus Area Courses

EE 5522 - Digital Image Processing

Fundamentals of image processing are covered including image representation, geometric transformations, binary image processing, compression, space and frequency domain processing. Computer programming in MATLAB and Python required.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall, Spring
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Computer Engineering

EE 5520 - Fourier Optics

Analysis and modeling of diffraction effects on optical systems, emphasizing frequency-domain analytic and computational approaches. Presents wave propagation, imaging, and optical information processing applications.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Fall
  • Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering
  • Pre-Requisite(s): EE 3190

EE 5532 - Sensing and Processing for Robotics

Sensing modes, signal and image processing for industrial robotic automation processes. Emphasis placed on widely used sensors, including cameras and 3-D sensors for process control and computer vision for autonomous navigation.

  • Credits: 3.0
  • Lec-Rec-Lab: (3-0-0)
  • Semesters Offered: Spring
  • Restrictions: Must be enrolled in one of the following Major(s): Electrical Engineering, Computer Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
  • Pre-Requisite(s): EE 5522

Advance Your EE Career

Enhance your electrical engineering career by opening new job opportunities with an advanced degree. Commit to growing your knowledge areas and to becoming an expert. Employers recognize advanced training—a master's degree may qualify you for leadership opportunities, project management responsibilities, or the chance to work on more complicated or sophisticated projects. Stand out by graduating from the #2 public university where grads make six figures (Money Magazine).


  • 30
    total credit hours to complete program
  • $3.5M
    in new research grants and contracts
  • $0
    applying online is always free
  • #6
    among the 30 Best Online Master's in Electrical Engineering

"The Michigan Technological University MSEE online program emphasizes communications and signal/image processing. In both of these areas the number of potential applications has vastly expanded over the past several years; however, the future for new applications of these technologies is almost unlimited. Digital communications have expanded to include wired and wireless communication between functional modules on cars and other complex machines, from vehicle-to-vehicle, and between vehicles and a variety of fixed infrastructures. The functionality of the present systems is fairly limited compared to what is envisioned for the future. Graduates of the Michigan Tech MSEE will be educated to create the future that these technologies afford."

Michael C. Roggemann Professor of Electrical Engineering and Computer Engineering
Michael C. Roggemann
Professor of Electrical Engineering and Computer Engineering