Graduate Certificate Programs in ECE

Graduate Certificate Programs in ECE

Graduate Certificate Programs

ECE department currently offers three certificates of grauduate studies (COGS), with additional ones under development.

Certificate of Graduate Studies in Machine Learning
Certificate of Graduate Studies in Power Systems Engineering
Certificate of Graduate Studies in Combat Systems Engineering


Certificate of Graduate Studies in

Machine Learning

Machine learning has been one of the fastest growing fields in all sciences and engineering. Not a day goes by that we hear another story that talks about how machine learning has become part of our lives. The number of applications where machine learning systems make automated decisions in place of humans have grown exponentially. There is a significant demand in this area for qualified professionals, and these professionals have some of the highest starting salary of any profession. Students graduating with a graduate degree in a machine learning related field typically receive salary offers that can reach $150,000 or higher.

The ECE Department has significant expertise in machine learning and has been regularly teaching related courses since 2001. This certifciate program puts the existing expertise and the courses together in one package allowing students to gain meaningful background that will prepare them for a career in machine learning and/or graduate programs. A unique aspect of this program is the practical project based experience that it provides: the program feature four classes, three of which are lecture based classes, each with its own project component. The fourth class can be a stand-alone project / research credit, where students will work on projects addressing real-world unsolved problems, many of which are externally funded. Hence, through this four-class sequence, the Machine Learning certificate program will provide breadth and depth in theoretical foundations of machine learning, as well as a year-long practical real-world project experience.

The completion of this certificate program will provide students with the necessary tools to start a career in machine learning as it applied to engineering, and/or continue their education through graduate programs. Due to rapid growth of machine learning as a well-established field of science and engineering, we expect the graduates of this program to find high-paying jobs and/or admission to further graduate programs.

This 12 credit graduate certificate program consists of the following courses:

Required Courses (2)

  • ECE 09.555 Advanced Topics in Pattern Recognition 

    and one of the following two

  • ECE 09.558 Reinforcement Learning 
  • ECE 09.595 Adv. Emerging Topics in Comp. Intelligence, Machine Learning and Data Mining 
Electives (choose any two of the following)
  • ECE 09.560 Artificial Neural Networks 
  • ECE 09.566 Systems, Devices and Algorithms in Bioinformatics
  • ECE 09.558 Reinforcement Learning 
  • ECE 09.655 Advanced Computational Intelligence and Machine Learning
  • ENGR 01.511 Engineering Optimization
  • ECE 09.595 Advanced Emerging Topics in Computational Intelligence, Machine Learning and Data Mining* or ECE 09.558 Reinforcement Learning*
  • ENGR 01.599 Master’s Thesis Research** or ENGR 01.799 Doctoral Research / Dissertation**  

*   Can be taken as an elective if not already taken as one of the required courses
** Permission of instructor is needed for students who are not in College of Engineering

Students applying to this COGS must have completed the following (or their equivalents) with a minimum GPA of 3.0, or must have relevant career experience that includes background in these courses.

  • A Bachelor of Science (or equivalent) degree in engineering, or a relevant area of science.
  • CS 04103 Computer Science and Programming or CS 04113 Introduction to Object Oriented Programming
  • MATH 01.235 Math for Engineering Analysis or (MATH 01.210 Linear Algebra and MATH 01.230 Calculus III)
  • STAT 02.290 Probability and Statistical Inference for Computing Systems or STAT 02360: Probability and Random Variables or STAT 02.286 Probability & Statistics for Electrical & Computer Engineering or equivalent background in probability and statistics.
  • Any prerequisites of the courses that make up this program.

(and undergraduate version of this program, Certificate of Undergraduate Studies (CUGS) in Applied Machine Learning in Engineering is also available)

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Certificate of Graduate Students in

Power Systems Engineering

The U.S. electricity grid is poised for a dramatic transformation, enabled by Smart Grid technologies, to address national and worldwide existential necessities: meeting the increasing electric energy needs, reducing the reliance on fossil fuels, and thus restoring and boosting the economy. The 2020 World Energy Outlook from the International Energy Agency estimates that the current value of the U.S. electricity grid is over $1 trillion, and the total cost of replacing it with a Smart Grid is $4~5 trillion. If a Smart Grid is fully deployed across the U.S., the country could expect to save $130 billion annually. The U.S. Department of Energy’s (DoE) Quadrennial Energy Review (QER) found that 1.5 million new jobs across the energy sector will need to be filled by 2030, with many of these positions paying 50 to 80 percent more than the average annual salary. However, achieving the goals of “Smart Grid” is hampered by a growing shortage of qualified electric power and energy engineers. With an aging workforce and looming retirements, the power and energy industry continually faces a hiring gap and reports that they cannot find skilled workers to fill open positions. According to the U.S. Senate Committee on Energy and Natural resources, 77% of energy companies find it difficult to hire qualified employees.

The Electrical and Computer Engineering Department has been regularly teaching power systems related graduate courses, and this COGS puts the existing ECE expertise and newly developed power systems courses together in one package allowing students to gain meaningful background that will prepare them for a career in power and energy area. It consists of four (4) graduate courses to develop graduates with a technical foundation in electric power systems focused on the operation of emerging systems, as described in below Program Curriculum. Through this four-class sequence, students will be able to articulate the core concepts of conventional system analysis, different renewable system analysis, electricity market and different smart grid enabling techniques. Additionally, one of the COGS electives could be a MS or PhD level research / thesis / dissertation, where students work on real-world power systems related problems under the supervision of faculty.

Overall, the Power Systems Engineering COGS will provide students with breadth and depth in theoretical foundations of emerging power systems, as well as practical hands-on project experience. As a result of this COGS, we expect our graduates to be particularly marketable, attracting many employers looking to hire highly qualified smart-grid ready power engineers. In addition, this COGS will give Rowan’s power program greater visibility and will improve our ability to attract students into the electrical and computer engineering program.

Program Structure: This program consists of four courses, two required and two electives, with a total of 12 credit hours. All required and elective courses are 3 credit hours each. One of the electives may be MS or PhD level research / thesis / dissertation, where the student will need to choose a power systems related topic for the project / research.

Required Courses

  1. ECE 09.504 ST ECE: Power System Engineering (3 cr). This class must be taken first.
  2. ECE 09.510 Advanced Alternate Energy Systems (3 cr)

Electives:

Choose either two courses (strongly recommended) from Knowledge Area 1 OR choose one from Knowledge Area 1 and one from Knowledge Area 2

Knowledge Area 1 (Courses with immediate relevance to Power Systems)

  • ECE 09.572 Advanced Smart Grid (3 cr)
  • ECE 09.573 Advanced Smart Sensors (3 cr)
  • ECE 09.515 Emerging Electricity Market (3 cr)

Knowledge Area 2 (supportive courses of relevance) – If only one course is taken from Knowledge Area 1, choose any one of the following. If you take two courses from Knowledge Area 1 (recommended), then the following is not required

  • ECE 09.585 Advanced Engineering Cyber Security (3 cr)
  • ECE 09.655 Advanced Computational Intelligence and Machine Learning (3 cr)
  • ECE 09.521 Fundamentals in Systems Engineering (3 cr)
  • ENGR 01.501 Engineering Economics (3 cr)
  • ENGR 01.511 Engineering Optimization (3 cr)
  • ENGR 01.598 Engineering Graduate Research (3 cr)
     One of the following can be used if the research is strictly related to Power Systems
  • ENGR 01.599 Master’s Research (3 cr)
  • ENGR 01.699 Doctoral Research and Dissertation (3 cr)
  • ENGR 01.799 Doctoral Research / Dissertation (3 cr)

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Certificate of Graduate Studies in 

Combat Systems Engineering

In collaboration with Lockheed Martin Company, the ECE department is now offering a new certificate program, called Certificate of Graduate  Studies (COGS) in Combat Systems Engineering (there is also a Certificate of Undergraduate Studies (CUGS) in Combat Systems Engineering (CSE), described in the ECE Curriculum section of our website). These certificate programs are intended to help develop the growing workforce needs of the area’s prominent defense industry. In fact, all classes are taught in cooperation with Lockheed Martin engineers. 

Active participation and successful completion of this program give students skills in analysis, design, evaluation, and validation of combat systems that are essential for all systems engineering jobs in the defense industry, and hence can dramatically increase your chances of getting one of those highly sought-after and well-paying defense industry positions.

The four courses in this program are

  • ECE 09.523           Advanced Radar Systems
  • ECE 09.524           Advanced War Gaming and C4ISR
  • ECE 09.525           Advanced Command and Control
  • ECE 09.526           Advanced Weapon Systems

Unlike the corresponding CUGS, there is no restriction regarding how many of these four graduate classes can be counted towards the MS in ECE program, and indeed all four of them can be used to satisfy the graduate degree program requirements, so long as they are approved by your graduate advisor. All thesis/dissertation students MUST, therefore, consult with their thesis advisors before registering for any of these classes to ensure that the classes fit into their program of study.

Please also see the Graduate Programs in Combat Systems Engineering brochure for additional details. 

Students applying to this COGS must have completed the following fundamental courses (or their equivalents) with a minimum GPA of 3.0, or must have relevant career experience that includes background in these courses.

  • A Bachelor of Science (or equivalent) degree in engineering, or a relevant area of science.
  • MATH 01.230 Calculus III
  • Any prerequisites of the courses that make up this program.

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