Take 3 or 6 credits for the capstone project.
- DSCI 8760 - Data Science M.S. Plan B Project
One of the key features of the M.S. in Data Science curriculum is a capstone project that makes the theoretical knowledge gained in the program operational in realistic settings.
Under the supervision of a faculty member, students will go through the entire process of solving a real-world problem: from collecting and processing real-world data, to designing the best method to solve the problem, and finally, to implementing a solution. The problems and datasets that students engage with will come from real-world settings identical to what you might encounter in industry, academia, or government. Examples of projects and the wide variety of topics they cover can be found on the research page, though this is only a partial list. Data-driven capstone projects may also grow from temporary internships at companies, with DGS approval.
Once students have confirmed who their faculty advisor will be, they should request a permission number for the capstone course (DSCI 8760) through our Declaration of Advisor form.
The Plan B project is completed under the guidance of a data science faculty member. Students are responsible for identifying and selecting their faculty advisor. Data Science M.S. students will present a final poster at the annual Poster Fair on their Plan B project as part of their degree requirements. The annual Poster Fair takes place every spring semester, and there will also be an opportunity for students to present in fall as needed. Students should then complete their written report as soon as possible following their poster presentation, which can be completed sometime in the subsequent semester if needed. If a report is not submitted and a final decision is not recorded by the subsequent semester’s program sponsored poster presentation opportunity, the student will be required to present a new poster to reflect updated work on their project. For example, a student who presents at the Spring poster fair should complete their written report by the next poster presentation event the subsequent Fall semester. Questions on this process can be directed to the Graduate Program Coordinator.
Committee requirements
Your M.S. degree committee must consist of three University of Minnesota-Twin Cities faculty members with formal graduate education responsibilities. Two committee members must be from the Data Science Program, including your advisor who serves as committee chair, and one committee member from an outside program
A qualified advisor from outside the data science faculty may be selected with DGS approval. You may be asked to provide a CV for that potential advisor. Your final project report will be approved by a committee of three faculty including your advisor and including at least one member of the data science faculty. If not already on the data science faculty, your advisor may like to join (they should send a short CV to the DGS), otherwise you will need to find a current member acting as a co-advisor to approve the final report. In any case, the three committee members should represent at least two different home departments. In other words, all three committee members cannot be from the same department. You will also be expected to give a short oral presentation on your project open to faculty, students, and other interested parties.
