All students must meet the Requirements for the Accelerated Master’s Degree Pathway
Overview
The accelerated M.S. in Complex Systems and Data Science (CSDS) is a 5-year degree coupled with a relevant bachelor's degree with optional disciplinary tracks. Our central goal is to help students become protean data scientists with eminently transferable skills. 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.
Specific Requirements
REQUIREMENTS FOR ADMISSION TO GRADUATE STUDIES FOR THE DEGREE OF MASTER OF SCIENCE FOR ACCELERATED STUDENTS
To be eligible for the Accelerated Master’s Entry Pathway, a student must be a declared computer science, mathematics, or statistics B.S. major, and have identified a Complex Systems faculty sponsor. Students need to apply early (before the second semester of their junior year) to have time to plan two graduate level courses that can be used toward both their bachelor's and graduate (M.S.) degree. These credits must be taken after formal admission to the graduate program. Other requirements include a GPA typically higher than 3.0 overall. All students must meet the Graduate college requirements for the Accelerated Master’s Degree Pathway. There is no GRE requirement.
MINIMUM DEGREE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE
A total of 30 credits, distributed as shown below:
| Common Core (3 Credits Each) | 12 | |
| CSYS 6701 | Principles of Complex Systms 1 (Include individual and/or team projects) | 3 |
| or MATH 6701 | Principles of Complex Systms 1 | |
| CSYS 6020 | Modeling Complex Systems (Include individual and/or team projects) | 3 |
| or CS 6020 | Modeling Complex Systems | |
| CSYS 5870 | Data Science I - Experience | 3 |
| or STAT 5870 | Data Science I - Experience | |
| or CS 5870 | Data Science I - Experience | |
| 1 of the following 3 courses: | 3 | |
| Principles of Complex Systms 2 | ||
| Special Topics (Modeling Complex Systems II) | ||
| Data Science II | ||
| Electives | 9 | |
| 6 credits of Complex Systems and/or Data Science Electives | 6 | |
| 3 credits of an advisor approved course | 3 | |
| Path Specific | 9 | |
Coursework only: 9 credits of either additional Complex Systems and Data Science courses or an elective path (Biomedical Systems, Distributed Systems, Energy Systems, Environmental Systems, Evolutionary Robotics, Policy Systems, or Self-designed named disciplinary path (requires approval of the CSDS advisor)) | ||
Coursework and project: 3 to 6 credits of project (CSYS 6392) plus additional 3 to 6 credits of course work | ||
Coursework and thesis: 6 to 9 credits of thesis research (CSYS 6391) plus additional 3 credits of course work if needed. | ||
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.
comprehensive exam
Students must demonstrate mastery of the material by one of four possible routes: an oral exam, a written exam, a paper, or a portfolio. The exact format will be decided upon by the Curriculum Committee in consultation with the student. The Curriculum Committee will also designate three relevant faculty who will create the exam and or specify the format and content area of the paper and assess the student’s performance.
REQUIREMENTS FOR ADVANCEMENT TO CANDIDACY FOR THE DEGREE OF MASTER OF SCIENCE
Successful completion of the comprehensive exam and all required coursework.