Masters in Complex Systems and Data Science
In a nutshell:
The Masters in Complex Systems and Data Science (CSDS) is a 2 year degree which trains emerging data scientists to find, model, understand, and tell the stories of the patterns they uncover.
The courework comprises a balanced core on Complex Systems and Data Science and includes choose-your-own adventure options.
Undergraduates may incorporate the degree as part of an Accelerated Master's Program (4 + 1 years).
We accept applications on a rolling basis for Fall entry with May 31 being a recommended soft deadline.
Students may also start in the Spring. International students will need to apply well in advance taking into consideration visa processes.
Please apply online through UVM's Graduate College.
More things to know:
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.
Our goal is to help students become protean data scientists with eminently transferable skills (read: super powers).
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.
Our educational foundation: The MS in CSDS is a natural expansion of our successful five course Graduate Certificate in Complex Systems which trains students from all disciplines to tackle data-rich problems.
Admissions requirements: Students must have a Bachelor’s degree in a relevant field and prior coursework in computer programming, calculus, probability, and statistics. Coursework in linear algebra and data structures are highly recommended but are not required for admission (students who are not from a Computer Science background and are lacking Data Structures will be required to take it as part of the degree). Students will also need to provide general GRE scores, a current resume/C.V., and three references.
Program director: Prof. Peter Dodds, Director of the Vermont Complex Systems Center.
Contact information: Please direct inquiries to Andrea Elledge, Associate Director of Operations and Outreach.
Key documents (pdf):
- Synopsis of the VCSC's MS in Complex Systems and Data Science.
- Guide to the course requirements and track options for the VCSC's MS in Complex Systems and Data Science.
Common core (4 courses, 12 credits): Students must pass comprehensive exams in these areas.
- 3 credits: CSYS/Math 300 Principles of Complex Systems.
- 3 credits: CSYS/CS 302 Modeling Complex Systems.
- 3 credits: Stat 287 Data Science I.
- 3 credits: Stat 387 Data Science II.
Disciplinary tracks: The MS in CSDS requires a minimum of ten three credit course. Three courses may be chosen by students to align with one of the following nine tracks:
- Pure CSDS.
- Energy Systems.
- Policy Systems.
- Biomedical Systems.
- Evolutionary Robotics.
- Environmental Systems.
- Transportation Systems.
- Distributed Systems Track.
- Self-designed named disciplinary track (requires approval of the CSDS curr comm)
For a full description of course requirements and track options, please refer to our Guide to the course requirements and track options for the VCSC's MS in Complex Systems and Data Science.
Core participating units at UVM:
- College of Engineering and Mathematical Sciences (CEMS).
- Department of Mathematics and Statistics.
- Department of Computer Science.
- Department of Electrical Engineering.
Optional tracks involve courses the following UVM colleges:
- College of Arts and Sciences (CAS).
- College of Agriculture and Life Sciences (CALS).
- Rubenstein School for Environment and Natural Resources (RSENR).
- College of Medicine (CoM).