Data-driven insights and analytics are facilitating and optimizing intelligent decision-making across industries.
Intended to meet the need for professionals who can harness complex data and convert it into meaningful information, the Master of Engineering in systems analytics provides students with expertise in visualizing, manipulating and extracting important concepts from systems data, complemented by training in traditional systems decision-making. The degree equips students with state-of-the art data visualization and knowledge extraction techniques for the purpose of analyzing trends, assessing risk, discovering patterns and building decision models that can better develop, maintain and improve complex engineering systems and enterprises.
The master’s degree requires 10 courses (30 credits) including six (6) core required courses and four (4) elective courses.
All elective courses must be approved by a faculty advisor.
Students are encouraged to select electives that lead to fulfillment of one of the many graduate certificates offered by the School of Systems & Enterprises.
Systems Analytics Required Core Courses
|EM 622 Data Analysis and Visualization Techniques for Decision Making
ES 630 Modeling and Visualization of Complex Systems and Enterprises (choose one)
|SYS 660 Decision and Risk Analysis||3|
|SYS 670 Forecasting and Demand Modeling Systems||3|
|ES 660 Multi-Agent Socio-Technical Systems||3|
|SYS 611 Modeling and Simulation
SYS 681 Dynamic Modeling of Systems and Enterprises (choose one)
|EM 623 Data Science and Knowledge Discovery in Engineering Management (3 credits)
FE 582 Foundations of Financial Data Science (2 credits)
FE 513 Practical Aspects of Database Design Lab (1 credit)
[Choose one 3-credit course or the combination offered in the second option.]