The Master of Science in Supply Chain Engineering (MSSCE) is a graduate degree program created to meet growing demand for business-savvy engineers who can design and synchronize highly-complex global supply chains. The program began in fall 2010 with an initial cohort of 12 transfer students from Panama. The first full class began in fall 2011, with 46 students who graduated in 2012. The program now graduates about 50 students each year, with approximately 275 program alumni as of summer 2017.
In August 2016, Amazon partnered with Georgia Tech and ISyE to introduce the MSSCE Systems Design track. The Systems Design track is designed to provide students with a deeper knowledge of designing systems both within the walls of a logistics facility and across facilities in a complex, ever-changing supply chain network. With $665,000 in funding over five years, the Systems Design track includes courses in mechatronics and robotics through Tech’s Woodruff School of Mechanical Engineering, ranked second nationally, as well as a course in industrial systems design.
The Amazon partnership funds four fellowships per year for students, who also receive priority for Amazon internships. The eight fellowship recipients thus far include an international contingent — one from Mexico, one from Belgium, and three from India — as well as two students from the U.S. Half of the recipients are female.
ISyE also is partially home to the new Online Master of Science in Analytics (OMSA). The OMSA, Georgia Tech’s second degree-at-scale, was announced in January 2017 on the edX platform. A collaboration between the Scheller College of Business and the Colleges of Engineering and Computing, the program is produced by Georgia Tech Professional Education and is offered for less than $10,000 tuition. Designed to be completed in one to two years, the OMSA offers the same interdisciplinary curriculum as the on-campus program, leveraging Georgia Tech’s strengths in statistics, operations research, computing, and business.
The first OMSA cohort began in August 2017, welcoming approximately 300 adult learners of which 26 percent have graduate degrees. The average age of this first cohort is 34, and 47 percent of the candidates are Georgia residents. This summer, Georgia Tech and edX also launched an Analytics MicroMasters© Program. The program has over 13,500 learners, 169 of which are in the verified track, progressing toward a completion certificate.
The machine learning (ML) Ph.D. program is a collaborative venture between Georgia Tech’s Colleges of Computing, Engineering, and Sciences through the Center for Machine Learning at Georgia Tech, an Interdisciplinary Research Center that is both a home for thought leaders and a training ground for the next generation of pioneers.
The ML Ph.D. began in August 2017. The initial class has 19 students, all drawn from incoming and current PhD. students from eight schools across three colleges at Georgia Tech: the Schools of Computational Science and Engineering, Computer Science, and Interactive Computing in the College of Computing; the Coulter Department of Biomedical Engineering, the School of Electrical and Computer Engineering, the Guggenheim School of Aerospace Engineering, and ISyE in the College of Engineering; and the School of Mathematics in the College of Sciences.
ML Ph.D. students are required to complete courses in five different areas: mathematical foundations, intermediate statistics, machine learning theory and methods, data models, and optimization. They are also required to take 15 hours of electives chosen from at least two of the following: statistics and applied probability, advanced theory, applications, computing and optimization, and platforms.
Stewart School of Industrial and Systems Engineering