An online master's degree in systems engineering is an excellent choice for some. Before pursuing a distance-based degree, it is important to keep certain considerations in mind.
Most online systems engineering master's programs may be completed without the student ever visiting the campus. This may be beneficial for some who don’t have physical access to a campus or are too busy to show up in person; however, it can also prove difficult for others who do not thrive outside the traditional classroom. Students pursuing a systems engineering degree online may not receive in-person support from peers or professors. In light of this, prospective students should be confident of their ability to succeed in a program with minimal physical oversight and assistance.
As mentioned before, an online master's program in systems engineering may be the ideal choice for a professional who wishes to pursue a degree while still working, for a parent with children, or even for someone who wants to attend a quality school but is not located nearby a campus that offers degrees in systems engineering.
Prospective systems engineering graduate students must meet various admissions standards before acceptance. And while the specifics may vary based on the institution, certain admission requirements generally stand across the board. In light of this, students interested in beginning an online master's in systems engineering should understand what to expect throughout the application process to ensure they are fully prepared.
Graduate applicants are often required to submit GRE scores, which are specific to graduate programs, although some online programs waive this requirement either entirely, or it is conditionally based on certain criteria such as academic background and grade point average (GPA).
In addition to this, graduate applicants may also be asked to submit letters of recommendation as well, which may be completed by college professors, employers, volunteer coordinators, or any other professional acquaintances who may be able to attest to the abilities of the applicant. Finally, many institutions will also ask for supplements to the application, including essays, proof of research, or other relevant documents.
In every case, applicants are required to submit their application on or before a certain deadline; while this varies by institution, in general, applications are due by January for those interested in starting in the fall, and by late fall for those applying to begin in the spring.
It is also important to understand that online students must still generally follow the same calendar as the rest of the campus; because of this, they must start the program at the same time as other traditional students. On occasion, an online master's program will offer additional start dates, including summer starts, but this varies by institution.
To demonstrate their quality and command respect in the field of engineering, many engineering schools take efforts to obtain credit through the Accreditation Board for Engineering and Technology (ABET), the official accrediting agency for engineering schools nationwide. ABET is further divided into separate societies based on branches of engineering, one of which is the International Council on Systems Engineering.
Accreditation is a voluntary process undertaken by the school and is a system of peer review that allows quality institutions to receive this mark of approval.
Pursuing a degree from an accredited program is, by no means, a requirement to work as a systems engineer in the future. However, professional licensure (the PE credential) is only awarded to those engineers who have completed a degree in a four-year accredited program. And this is significant; professional engineers, who are awarded licensure by the National Society of Professional Engineers (NSPE), can “shoulder the responsibility for not only their work but also for the lives affected by that work,” and is a “legal requirement for those who are in responsible charge of work.” In addition, most states require engineering professors or instructors to obtain professional licensure before teaching.
Those who pursue a degree in systems engineering will generally follow a similar curriculum, regardless of their institution of study. Students are generally required to take courses in mathematics and computer science, as well as those on the subject of core systems. Graduate systems engineering students typically have a specialized systems engineering curriculum devoid of some of the general education requirements typical in an undergraduate program.
In some cases, students who are pursuing a degree in systems engineering may be able to obtain certain specializations or certificates related to the field. Specifically, students may be able to specialize in:
While pursuing an online degree in systems engineering may be a relatively new concept, obtaining such a degree from several esteemed institutions is still possible. Students wishing to achieve a high-quality education in the SE field may consider applying to one of the five highly regarded programs.
Colorado State University allows students to pursue either a master of science (MS) or a master of engineering (MEng) degree in systems engineering. This program allows students to learn solely online, or attend classes on campus if they choose. Both these degrees have content covering management and technical processes to systems design. The faculty for the program includes renowned professionals with a vast body of research and real-world experience.
Common admission requirements for both degrees include a bachelor of science degree from a regionally accredited institution, a grade point average of 3.0, knowledge of basic statistics and calculus, three letters of recommendation, a current resume, a statement of purpose, a completed online application, and one official transcript of all collegiate work completed from every institution attended. International students are required to submit TOEFL or IELTS or PTE scores.
Made up of 30 credits, some courses in the curriculum include the foundations of systems engineering; an overview of systems engineering processes; engineering risk analysis; software development methodology; electrical power engineering; systems requirements engineering; and systems engineering architecture.
The program equips students with skills that can be applied across industries, such as energy, healthcare, aerospace, and automotive. Students will develop expertise in the fields of management, mathematics, and engineering, and learn how to implement and design solutions to complex issues. They prepare for a wide variety of systems engineering careers such as government and military sectors, healthcare systems, power and energy, computer networks, information systems, and cyber security.
Arizona State University offers an online master of engineering (MEng) in systems engineering program. This fully online program allows students to engineer complex processes, services, and products while leveraging a systems engineering approach. This program is ideal for professionals who lead major complex systems development or programs at their companies.
The major admission requirements include a bachelor's or master's degree in software engineering, computer engineering, or a related subject; a minimum grade point average of 3.0; a completed graduate admission application; official transcripts; and proof of English proficiency for applicants whose native language is not English. GRE scores are not required.
Comprising 30 credits, the program comprises ten courses, including advanced quality control; design of experiments; engineering administration; enterprise modeling; introduction to systems engineering; project management; reliability engineering; risk management; nonlinear control systems; production systems; and software verification and validation.
At the end of the program, graduates can be qualified to work in information technology, transportation, operations, aerospace, and manufacturing.
The University Of Arizona offers an online master of science (MS) in systems engineering program. The program examines the modeling, analysis, and design of various components of advanced systems. Students will be able to design practical solutions alongside their professors and learn how to maximize efficiency in all their processes. The program's focus is ensuring that projects are within a budget, meet all necessary requirements, and are reliable for several years.
To get accepted into the program, applicants must have graduated from an accredited engineering bachelor’s program or have earned a degree in a related discipline, have a minimum grade point average of 3.0, and submit the graduate admissions application, three letters of recommendation, a brief statement of intent, an updated resume or CV, and unofficial transcripts from all universities or colleges attended.
The curriculum for the program is flexible and allows students to choose electives that align with their career goals. They also have the freedom to choose how they would like to complete program requirements, whether in the form of a research project, a faculty-guided thesis, or practical coursework.
The core coursework, comprising nine credits, explores topics such as systems engineering processes, linear systems theory, and stochastic modeling. The project and the thesis options comprise 30 credits each, while the coursework-only option comprises 33 credits.
The program helps students develop skills in reliability testing, quality control, statistics, stochastic modeling, linear systems, project management, and financial modeling.
The Missouri University of Science and Technology offers an online master’s degree and a doctorate in systems engineering. The master’s program helps engineering managers and engineers develop advanced skills and knowledge to confidently develop and implement complex systems. As an added incentive, students can earn two graduate certificates in any of the following emphasis areas: systems engineering; network-centric systems; model-based systems engineering; and computational intelligence.
Applicants to the master’s program must have a bachelor’s degree in computer science, engineering, applied mathematics, or physical science, and an undergraduate grade point average of 3.0. Admission requirements for the PhD program include an MS in systems engineering (or related field) with a grade point average of 3.5 and a minimum of three years of full-time work experience beyond the bachelor's degree. Common requirements for both programs include GRE scores, and TOEFL or IELTS scores for international applicants.
The master’s program offers a thesis (36 credits) and non-thesis (30 credits) option. For the PhD program, students must complete only 54 credits if they have already completed a master’s degree in systems engineering. (If students are directly pursuing a PhD degree after a BS degree, then they need to complete 84 credits.)
The MS program includes instruction in systems engineering and analysis; information-based design; systems life cycle costing; and systems architecting. The PhD offers courses such as advanced research methodologies; systems architecting; optimization under uncertainty; and mathematical programming.
Texas Tech University offers an online master of science (MS) in systems and engineering management degree program. The program prepares engineering managers and industrial engineers for successful careers in consulting, industry, research, and university teaching. There is a growing demand for highly technical managers with a sound understanding of management and finance, and the program aims to fulfill it. Offered both online and on-campus, this program offers students with a non-industrial engineering degree to get graduate training in engineering management and their chosen specialty.
The major admission requirements for the program include official transcripts, diplomas/degree certificates, test scores, a statement of purpose, recommendations, writing samples, and a creative portfolio, among other requirements.
The program comprises 30 credits and includes courses such as the engineering management environment; decision theory and management science; systems theory; simulation models for operations analysis; and optimization principles.
Through the program, students learn how to identify, formulate, and solve complex engineering problems by applying engineering, science, and mathematics principles. They also learn how to communicate effectively with a range of audiences, recognize ethical and professional responsibilities in engineering situations, and make informed judgments. Overall, they are trained to develop and conduct experiments, analyze data, and use engineering judgment to draw conclusions.
In general, campus visitation requirements for online systems engineering master's programs will vary depending on the school. Some may require the students to attend once per semester to complete exams, while others may allow the student to complete the degree without ever setting foot on campus.
For many institutions, the latter is true; for example, a degree at Missouri University of Science and Technology may be obtained through courses delivered online, and without any in-class instruction. Because of this variance across schools, prospective students should familiarize themselves with specifics in order to be prepared for what to expect.
There are several other considerations that prospective students should keep in mind before deciding on pursuing an online master's degree in systems engineering.
Most importantly, students should research whether or not the institution assists students with job placement after graduation; many schools offer career counseling programs, which can be highly beneficial for those students searching for post-graduation employment.
Students may wish to discuss these and any other questions or concerns with an admissions officer before applying to the program. Doing this can help ensure that the prospective student knows what to expect from the degree program before applying.
Ronald Askin, PhD - Arizona State University
Dr. Ronald Askin is a professor of industrial engineering in the School of Computing and Augmented Intelligence at Arizona State University. His research interests include production logistics, applied operations research, manufacturing systems analysis, and applied statistics. He teaches or has taught classes on advanced manufacturing systems modeling; computer-integrated manufacturing systems; integrated product and process development methodologies; and production systems analysis.
Professor Askin has published in journals such as the International Journal of Production Research and the European Journal of Operational Research. He also has won numerous awards such as the Albert G. Holzman Distinguished Educator Award and a Distinguished Alumni Award. He earned his PhD and MS from the Georgia Institute of Technology, and a BS from Lehigh University.
Thomas Bradley, PhD - Colorado State University
Dr. Thomas H. Bradley is a department head and Woodward systems engineering professor at Colorado State University. His research focuses on energy system management applications, life cycle assessment, and automotive and aerospace system design. He teaches or has taught courses such as leadership/innovation in systems engineering and research methods and systems engineering.
His work has appeared in influential journals such as Environmental Science & Technology, the Journal of Power Sources, and Bioresource Technology. He completed his PhD at the Georgia Institute of Technology, and MS and BS degrees at the University of California at Davis.
Suman K. Chowdhury, PhD - Texas Tech University
Dr. Suman K. Chowdhury is an assistant professor in the Department of Industrial, Manufacturing, and Systems Engineering at Texas Tech University. He teaches or has taught courses such as engineering design for people; advanced industrial ergonomics & accompanying distance section; biomechanics and work physiology & accompanying distance section; and experimental methods in biomechanics and work physiology. His research focuses on the neural control of the musculoskeletal system, virtual reality applications in injury biomechanics, traumatic brain injuries and helmet design, multiscale computational biomechanics, and ballistic impact and fluid-structure interaction analysis.
Dr. Chowdhury has published in journals such as the Journal of Electromyography and Kinesiology, the International Journal of Industrial Ergonomics, and Human Factors. He holds his PhD and MS from West Virginia University and a BS from Bangladesh University of Engineering and Technology.
Steven Corns, PhD - Missouri University of Science and Technology
Dr. Steven Corns is an associate professor and associate chair within the Department of Engineering Management and Systems Engineering at the Missouri University of Science And Technology. He teaches or has taught courses such as introduction to complex systems management; systems engineering and analysis; and computational intelligence. His research interests include computational intelligence, bioinformatics, autonomous systems, infrastructure system modeling, and complex systems.
Dr. Corns has published in impactful scholarly journals such as Neural Networks, Systems Engineering Journal, and the Data Science Journal. He holds a PhD, an MS, and a BS in mechanical engineering—all from Iowa State University.
Cihan H. Dagli, PhD - Missouri University of Science and Technology
Dr. Cihan H. Dagli is a Missouri University of Science and Technology professor. As the director and founder of systems engineering programs, he teaches classes on neural networks and applications, systems architecting, deep learning and advanced neural networks, and smart engineering systems design. His research interests include cyber-physical systems, systems engineering and architecting, machine learning and computational intelligence, and deep learning.
Dr. Dagli's work has appeared in renowned journals such as the Journal of Intelligent Manufacturing, the International Journal of Production Research, and the International Journal of Production Economics. He holds his PhD from the University of Birmingham, and his MS and BS from Middle East Technical University.
Neng Fan, PhD - University of Arizona
Dr. Neng Fan is an associate professor at the University of Arizona, in the systems and industrial engineering department. His teaching interests include operations research, optimization, statistics, probability, machine learning, and data analytics.
Dr. Fan’s research interests include stochastic and robust optimization methods and their applications in data mining; integer programming; combinatorial optimization; water systems; healthcare; and energy systems. Professor Fan has published in respected journals such as the European Journal of Operational Research, the Journal of Global Optimization, and the Annals of Operations Research. He completed his PhD in industrial and systems engineering, MS in industrial and systems engineering from the University of Florida, and a BS in computational mathematics and MS in applied mathematics from Wuhan University.
Roberto Furfaro, PhD - University of Arizona
Dr. Roberto Furfaro is a professor in the department of systems and industrial engineering at the University of Arizona. Having published over 50 peer-reviewed journal papers and more than 200 conference papers and abstracts, Dr. Furfaro has a wide range of expertise and has been working on several projects such as the development of guidance navigation and control of planetary landers, machine learning applications to space situational awareness, and systems engineering for close-proximity operations on small bodies.
Dr. Furfaro’s work has been published in top journals such as the Annals of Nuclear Energy, the Astrophysical Journal, and the Journal of Computational and Theoretical Transport. He completed his PhD in Aerospace Engineering at the University of Arizona.
Timothy Matis, PhD - Texas Tech University
Dr. Timothy Matis is an associate professor in the Department of Industrial, Manufacturing, and Systems Engineering at Texas Tech University. He has taught courses such as principles of optimization; applied stochastic processes; theoretical studies; design of experiments; and reliability theory. His research interests include operations research, queuing theory, stochastic processes, and ad-hoc communication networks.
Dr. Matis’s work has appeared in the Journal of Applied Research and Technology and the International Journal of Production Economics. He earned his PhD, MS, and BS from Texas A&M University.
Erika Miller, PhD - Colorado State University
Dr. Erika Miller is an assistant professor of systems engineering at Colorado State University. She teaches or has taught courses such as engineering risk analysis; human systems integration; and engineering data analytics. Her research is primarily centered on integrating humans with complex systems to enhance safety and performance in designing and evaluating new and existing infrastructure. Her research and educational background are in systems, industrial, civil, and transportation engineering. She earned her BS from Oregon State University and an MS and PhD from the University of Washington.
Pitu Mirchandani, ScD - Arizona State University
Dr. Pitu B. Mirchandani is a computing and augmented intelligence professor at Arizona State University. His expertise includes decision-making under uncertainty, optimization, real-time control and logistics, transportation, and homeland security.
Dr. Mirchandani has published in prominent journals such as Transportation Science, the European Journal of Operational Research, and the Annals of Operations Research. He completed his MS and BS at UCLA and his ScD and SM from the Massachusetts Institute of Technology.
Meet several top professors of systems engineering who teach at well-regarded universities, and who contribute both to the field of systems engineering and to the knowledge of students in their respective programs.