MS/SE Concentration in
Systems Engineering and Data Analytics (SEDA)

Systems Engineers must address a broad range of issues relevant to the design, implementation, analysis and management of systems. This emphasis provides the student with methodological tools that can be applied to the systems engineering process. Areas of focus include decision support systems, distributed intelligent systems, knowledge-based planning systems, network systems, probabilistic reasoning systems, sensor fusion systems, and optimization methods. The graduate program in Systems Engineering recognizes the importance of a balancing an education in quantitative models and engineering tools with a proper understanding of the systems perspective.

Basic methods course:
Students must complete the following:

• OR 541 - Operations Research: Deterministic Models

Concentration-specific courses:
Students must complete one required course and two elective courses from an approved list. The required course is:

• SYST 568 - Applied Predictive Analytics

The list of approved elective includes all basic methods courses and the following:

• SYST 538 Analytics for Financial Engineering and Econometrics
• SYST 584 Heterogeneous Data Fusion
• SYST 618 Model-based Systems Engineering
• SYST 621 Systems Architecture Design and Evaluation
• SYST 671 Judgment and Choice Processing and Decision Making
• SYST 683 Modeling Simulation and Gaming
• OR 603 Sports Analytics
• OR 604 Practical Optimization