M.S. in Electrical Engineering

The Master of Science degree in Electrical Engineering at the University of St. Thomas is a hands-on, industry-oriented and career-focused graduate program that blends theory and research with practical engineering fundamentals. Designed with considerable input from industry, the electrical engineering master's degree program provides our graduates with the in-depth technical skills necessary to succeed in a rapidly changing world and make immediate meaningful contributions to the technical vitality of the state of Minnesota.

The St. Thomas Master of Science degree in Electrical Engineering program has two options that are each worth 30 graduate credits: a course-based path, which requires completion of 10 graduate-level courses (30 credits), or a project-based path which requires completion of 8 courses (24 credits) and a design project (6 credits). This master's program can be pursued part-time or full-time with classes  that meet weeknights and are designed to meet the needs of working professionals.

Graduate electrical engineering students focus their study in a particular area of electrical and computer engineering by choosing one of the following concentration areas: Power Systems, Smart Grid and Electric Vehicles, Communications and Signal Processing, or Embedded Systems and Internet of Things (IoT).

  • The Power Systems concentration emphasizes the study and control of power systems, distribution, renewable energy, electrical machines and power electronics. Power electronics enables the economic viability of renewable energy systems via its ability to transform electrical energy in one form to another with near 100% efficiency.
  • The Smart Grid and Electric Vehicles concentration will prepare students to meet the challenges of the 21st century electric grid. Power engineers will lead the way in decarbonizing the electric grid and electrifying the transportation industry.
  • The Communications and Signal Processing concentration focuses on the study of communication and processing of information, which is the foundation for all of our digital lives. Applications can be found in all areas around us such as IoT, wearables, mobile health care, autonomous vehicles, Artificial Intelligence, and communication of such information over a variety of communication networks such as Wifi, Bluetooth, 4G LTE, and 5G wireless networks.
  • The Embedded Systems and Internet of Things (IoT) concentration enables students to become proficient with microcomputers, sensors, interconnections and their composite systems used to design and control devices impacting many aspects of our daily lives from smart homes and cars to pacemakers and wearable devices.
  • A bachelor's degree from a regionally-accredited educational institution in the U.S. (or international equivalent).  Engineering and physics majors can finish the M.S. in Electrical Engineering program in two years.

  • An overall grade-point-average (GPA) of at least 2.7 out of 4.0. (Applicants with a GPA less than 2.7 will be considered for provisional admission with their professional experience factored into the decision.)

To complete the requirements for the Master of Science in Electrical Engineering, students must successfully complete 10 courses (30 graduate semester credits) and maintain a GPA of at least 2.7.

REQUIRED CORE COURSES (5 courses = 15 credits)

  • ETLS 744 Power Systems and Smart Grids
  • ETLS 746 Power Electronics
  • ETLS 747 Electrical Machines and Vehicles
  • ETLS 748 Renewable Energy Generation
  • ETLS 810 Advanced Controls

TECHNICAL ELECTIVES (5 courses = 15 credits)

Choose five technical electives from course list below:

  • ETLS 620 Analog Communication Systems
  • ETLS 621 Digital Communication Systems
  • ETLS 630: Sensors for the Internet of Things (IoT) and Autonomy
  • ETLS 631 Wireless Sensor Networks
  • ETLS 675 Digital Signal Processing
  • ETLS 676 Real Time DSP
  • ETLS 678 Wearable Systems, Data and IoT
  • ETLS 679 Embedded & Cyber Physical Systems
  • ETLS 699 Selected Topics
  • ETLS 739 EV Market and Technologies
  • ETLS 745 Power Systems Operations And Controls
  • ETLS 753 Power Systems Protection and Relay
  • ETLS 750 Smart Distribution Systems
  • ETLS 751 Electromagnetic Fields And Waves
  • SEIS 631 Foundations of Data Analysis
  • SEIS 663 Information Technology Security and Networking
  • SEIS 763 Machine Learning
  • SEIS 764 Artificial Intelligence
  • ETLS 881 Engineering Project Credits (2 consecutive semester of 6 credits total )

REQUIRED CORE COURSES (5 courses = 15 credits)

  • ETLS 744 Power Systems and Smart Grids
  • ETLS 746 Power Electronics
  • ETLS 747 Electrical Machines and Vehicles
  • ETLS 739 EV Market and Technologies
  • ETLS 750 Smart Distribution Systems

TECHNICAL ELECTIVES (5 courses = 15 credits)

Choose five electives from the courses listed below:

  • ETLS 620 Analog Communication Systems
  • ETLS 621 Digital Communication Systems
  • ETLS 630: Sensors for the Internet of Things (IoT) and Autonomy
  • ETLS 631 Wireless Sensor Networks
  • ETLS 675 Digital Signal Processing
  • ETLS 676 Real Time DSP
  • ETLS 678 Wearable Systems, Data and IoT
  • ETLS 679 Embedded & Cyber Physical Systems
  • ETLS 699 Selected Topics
  • ETLS 745 Power Systems Operations And Controls
  • ETLS 748 Renewable Energy Generation
  • ETLS 751 Electromagnetic Fields And Waves
  • ETLS 753 Power Systems Protection and Relay
  • ETLS 810 Advanced Controls
  • SEIS 631 Foundations of Data Analysis
  • SEIS 663 Information Technology Security and Networking
  • SEIS 763 Machine Learning
  • SEIS 764 Artificial Intelligence
  • ETLS 881 Engineering Project Credits (2 consecutive semester of 6 credits total )

REQUIRED COURSES (5 courses = 15 credits)

  • ETLS 620 Analog Communication Systems
  • ETLS 621 Digital Communication Systems
  • ETLS 631 Wireless Sensor Networks
  • ETLS 675 Digital Signal Processing
  • ETLS 678 Wearable Systems, Data and IoT

TECHNICAL ELECTIVES (5 courses = 15 credits)

Choose five electives from the course list below:

  • ETLS 630: Sensors for the Internet of Things (IoT) and Autonomy
  • ETLS 676 Real Time DSP
  • ETLS 679 Embedded & Cyber Physical Systems
  • ETLS 699 Selected Topics
  • ETLS 739 EV Market and Technologies
  • ETLS 744  Power Systems and Smart Grids
  • ETLS 745 Power Systems Operations And Controls
  • ETLS 746 Power Electronics
  • ETLS 747 Electrical Machines
  • ETLS 748 Renewable Energy Generation
  • ETLS 750 Smart Distribution Systems
  • ETLS 751 Electromagnetic Fields And Waves
  • ETLS 753 Power Systems Protection and Relay
  • ETLS 810 Advanced Controls
  • SEIS 631 Foundations of Data Analysis
  • SEIS 663 Information Technology Security and Networking
  • SEIS 763 Machine Learning
  • SEIS 764 Artificial Intelligence
  • ETLS 881 Engineering Project Credits (2 consecutive semesters of 6 credits total )

REQUIRED COURSES (5 courses = 15 credits)

  • ETLS 676 Real Time DSP
  • ETLS 679 Embedded & Cyber Physical Systems
  • ETLS 630: Sensors for the Internet of Things (IoT) and Autonomy
  • ETLS 631: Wireless Sensor Networks
  • ETLS 678 Wearable Systems, Data and IoT

TECHNICAL ELECTIVES (5 courses=15 credits)

Choose five electives from the course list below:

  • ETLS 620 Analog Communication Systems
  • ETLS 621 Digital Communication Systems
  • ETLS 675 Digital Signal Processing
  • ETLS 699 Selected Topics
  • ETLS 739 EV Market and Technologies
  • ETLS 744  Power Systems and Smart Grids
  • ETLS 745 Power Systems Operations And Controls
  • ETLS 746 Power Electronics
  • ETLS 747 Electrical Machines
  • ETLS 748 Renewable Energy Generation
  • ETLS 750 Smart Distribution Systems
  • ETLS 751 Electromagnetic Fields And Waves
  • ETLS 753 Power Systems Protection and Relay
  • ETLS 810 Advanced Controls
  • SEIS 631 Foundations of Data Analysis
  • SEIS 663 Information Technology Security and Networking
  • SEIS 763 Machine Learning
  • SEIS 764 Artificial Intelligence
  • ETLS 881 Engineering Project Credits (2 consecutive semesters of 6 credits total )

Please meet with your advisor for this program, Dr. Greg Mowry, early in your program to determine the best class sequence, as some classes are only offered bi-annually.  


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