Overview

Overview#

The Capstone course and project provide a unique opportunity to apply the foundational knowledge gained from your first year of coursework to address real-life problems and challenges for a partner organization over the course of a full academic year. The purpose of a capstone project is for you to develop and communicate a data-driven solution to an organization’s problem from project ideation and definition through delivery. Your project will demonstrate the challenges and pitfalls faced by a professional data scientist and to provide an environment to overcome the problems you encounter.

The course component will include graded assignments related to your project or your ability to communicate. The course grade will also account for how you collaborate outside partners; how you acquire, organize, and process the data; how you create a machine learning, statistical, and/or mathematical approach to solve the questions at hand; how you implement your approach; how you present and communicate your findings; and the curiosity and creativity you portray throughout the year as you’re solving the problem.

Course Rhythm#

Fall 2026

Scope, plan, and build momentum

Teams clarify requirements, establish working agreements, meet clients, and present progress throughout the semester.

Spring 2027

Refine, communicate, and showcase

Teams polish deliverables, strengthen presentation materials, prepare posters, and present at the symposium.

Core Emphasis#

  • Technical execution on authentic data science problems

  • Client and mentor communication

  • Teamwork and conflict-resolution habits

  • Professional development and presentation craft

  • Iterative delivery based on feedback

Expectations#

The Capstone Project serves as your Master’s thesis and should be treated as such. This is a graduation requirement and should be given equal weight to job interviews and other classes. On average, you should be putting in at least 12 hours of work per week per student. This includes time spent in class, meetings, and any assignments.

  • Maintain regular communication with clients and mentors

  • Actively incorporate feedback into project development

  • Demonstrate professionalism, accountability, and teamwork

  • Deliver high-quality technical and presentation outputs

You should always respect your classmates and teammates. This applies not only to how you speak and communicate with others, but also to respecting each other’s time and effort.

Faculty Mentors#

Each Capstone team is assigned a Faculty Mentor. These mentors will meet with you regularly throughout the year and provide guidance and advice when you are stuck. You should consider your mentor as a resource to ask questions and receive feedback. It is essential that you are proactive in seeking help if you are in need. Additionally, you may contact the Capstone Director if you need any further assistance that your Mentor cannot provide.

Teams are expected to keep clients and mentors informed, document decisions, and show steady progress across both semesters. The capstone is not only a technical project, it is also a rehearsal for collaborative data science work in professional settings.

Key Components#

  • Major Deliverables

    • Team Progress, Client Requirements & Task Breakdown

    • Team Contract (communication + conflict resolution)

    • Progress Presentations (4 total per semester)

    • Poster, Capstone Symposium, and Final Client Deliverables

  • Professional Development

    • Story Circles

    • Leadership & teamwork training

    • Guest speaker or domain expert engagement

  • Feedback & Iteration

    • Continuous mentor/client feedback

    • Iterative refinement throughout the project lifecycle

Plan

Align on scope, requirements, and the work system your team will use.

Build

Execute technical work while maintaining regular client communication.

Present

Share progress, integrate feedback, and prepare final symposium.

Grading Policy#

All grades will be calculated based on the following letter grade scale:

Letter Grade

Percentage Range

A+

Exceptional performance only and > 97%

A

99% - 93%

A-

< 93% - 90%

B+

< 90% - 87%

B

< 87% - 83%

B-

< 83% - 80%

C+

< 80% - 77%

C

< 77% - 73%

C-

< 73% - 70%

D+

< 70% - 67%

D

< 67% - 63%

D-

< 63% - 60%

F

< 60%