Complex Systems and Data Science M.S.
All students must meet the Requirements for the Master's Degree
The Vermont Complex Systems Center’s MS in CSDS is a two year degree with optional disciplinary tracks. UVM undergraduates may incorporate the degree as part of an Accelerated Master’s Program. Our central goal is to help students become protean data scientists with eminently transferable skills (read: super powers). We provide students with a broad training in computational and theoretical techniques for (1) describing and understanding complex natural and sociotechnical systems, enabling them to then, as possible, (2) predict, control, manage, and create such systems. Students will be trained in: Industry standard methods of data acquisition, storage, manipulation, and curation; Visualization techniques, with a focus on building high quality web-based applications; Finding complex patterns and correlations through, for example, machine learning and data mining; Powerful ways of hypothesizing, searching for, and extracting explanatory, mechanistic stories underlying complex systems—not just how to use black box techniques; Combining the formulation of mechanistic models (e.g., toy physics models) with genetic programming.
REQUIREMENTS FOR ADMISSION TO GRADUATE STUDIES FOR THE DEGREE OF MASTER OF SCIENCE
Our program aims to serve students coming from a wide variety of backgrounds and therefore deliberately keep the prerequisites to a minimum. Students must have a Bachelors degree in a relevant field and prior coursework in computer programming, calculus, probability, and statistics. Linear algebra is highly recommended but not required. Please note that some electives have additional prerequisites. General GRE scores are required.
MINIMUM DEGREE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE
A total of thirty credits, distributed as shown below:
|Common Core (4 courses)||12|
|CSYS 300||Principles of Complex Systems (Include individual and/or team projects)||3|
|or MATH 300||Principles of Complex Systems|
|CSYS 302||Modeling Complex Systems (Include individual and/or team projects)||3|
|or CS 302||Modeling Complex Systems|
|STAT 287||Data Science I (Include individual and/or team projects)||3|
|STAT 387||Data Science II (Include individual and/or team projects)||3|
Students who receive a grade of A- or above will not be required to take oral exams. Those who fall below this mark will have oral exams involving three faculty
Six credits of Complex Systems and/or Data Science Electives
Three credits of an advisor approved course
Nine credits in a concentration track (Enery Systems, Policy Systems, Biomedical Systems, Evolutionary Robotics, Environmental Systems, Distributed Systems Track, Self-designed track)
A Policy Systems Elective is recommended for students in the Energy Systems Track.
CS 124: Data Structure is required and is approved for graduate credit (pending completion of a Permission to take a 100/200 Level Course for Graduate Credit Form) for those without a formal CS background unless candidates can establish competency in this area.
Threaded throughout their courses, a desired central outcome of each Master’s student’s training will be their development of a data-intensive, high design portfolio of interactive online visualizations. Students will have many opportunities to work with faculty, researchers, institutions, and corporations, on meaningful, important real-world data sets, drawn from engineering systems, neuroscience, society through the lens of social media, and more. Beyond being a key training mechanism, we envisage these portfolios—in the manner of, for example, a traditional engineering design or artist’s set of works—will be instrumental in students achieving outstanding positions in their chosen fields.
Receiving an A- or above in all four core courses meets the comprehensive exam requirement. Students who fall below this mark will have oral exams involving three faculty organized by the Curriculum Committee.
REQUIREMENTS FOR ADVANCEMENT TO CANDIDACY FOR THE DEGREE OF MASTER OF SCIENCE
Successful completion of the comprehensive exam and all required coursework.