Master of Engineering in Systems Analytics
Data-driven insights and analytics are facilitating and optimizing intelligent decision-making across industries today. Intended to meet the need for professionals who can harness complex data and convert it into meaningful information, the master’s in systems analytics at the School of Systems and Enterprises is providing students with expertise in visualizing, manipulating and extracting important concepts from systems data, and complementing it with traditional systems decision-making. The master’s 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.
This master’s degree consists of ten courses (30 credits): six required core courses and four electives as described below.
Systems Analytics Curriculum
Required Core Courses
| EM 624 | Data Exploration and Informatics for Engineering Management | 3 |
| EM 622 | Decision Making Via Data Analysis Techniques | 3 |
| SYS 660 | Decision and Risk Analysis | 3 |
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| EM 623 | Data Science and Knowledge Discovery | 3 |
| Or | |
| EM 626 | Applied AI & Machine Learning for Systems and Enterprises | 1 |
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| EM 633 | Decision Sciences and Data Analytics in Healthcare | 3 |
| Or | |
| SYS 670 | Forecasting and Demand Modeling Systems | 3 |
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| SYS 682 | Multi-Agent Socio-Technical Systems | 3 |
| Or | |
| SYS 611 | Systems Modeling and Simulation | 3 |
Elective Courses
Students are encouraged to take an integrated four-course sequence leading to a graduate certificate for the four electives, or choose the electives from the course catalog. All elective courses must be approved by an advisor. A list of available graduate certificates is included in this catalog and on the School of Systems and Enterprises website.