MSBAi Capstone/Practicum
Program-level details: See program/CURRICULUM.md
Credits: 4 | Term: Spring 2028, Weeks 1-8 | Instructor: TBD
Overview
The capstone is the culminating experience of the MSBAi program. It is split into two parts: portfolio assembly (demonstrating cumulative learning, individual) and an applied team client project (demonstrating new independent work). Students complete both parts within a single 8-week course.
Structure
Part 1: Portfolio Assembly (Weeks 1-2, Individual)
Students curate and refine their best work from across the program into a professional portfolio.
Deliverables:
- Select 3-4 best projects from all MSBAi courses
- Write reflection narratives for each selected project (what was learned, what would be done differently)
- Create public GitHub portfolio with polished repos, README files, and documentation
- Practice and deliver a portfolio pitch (3 minutes)
Assessment Focus: Quality of curation, reflection depth, portfolio presentation, GitHub professionalism.
Part 2: Applied Client Project (Weeks 3-8, Team of 3-4)
Student teams complete a new analytical project with an external client or as independent research. Teams have a rotating project lead role (each member leads for 1-2 weeks).
Project Options:
- Option A (Recommended): Real consulting project via Research Park partnership or corporate sponsor
- Option B: Independent team research on a self-selected business problem with real-world data
Team Structure:
- Teams of 3-4 students assigned by instructor (balanced skill sets)
- Rotating project lead (each member leads for 1-2 weeks)
- Weekly team check-ins with faculty advisor
- Peer evaluation at midpoint and end
Deliverables:
- GitHub repository with documented, reproducible code
- Jupyter Notebook(s) with analysis, visualizations, and narrative
- Executive summary (2-page memo for non-technical audience)
- AI usage documentation (how AI tools were used, where human judgment was applied)
- AI Governance & Risk section (risk assessment, ethical considerations, model limitations)
- Oral defense: 20-min panel presentation + 10-min defense Q&A (weighted 40-50% of capstone grade)
Assessment Focus: Technical rigor, business insight, communication quality, code reproducibility, ethical AI use, team collaboration.
Assessment Summary
| Component | Weight | Format |
|---|---|---|
| Portfolio Assembly (Part 1) | 20% | Individual |
| Client Project Deliverables (Part 2) | 30-40% | Team |
| Oral Defense (Part 2) | 40-50% | Team (panel presentation + Q&A) |
Oral Defense Details:
- 20-min presentation to faculty panel (and client sponsor, if applicable)
- 10-min Q&A where panel probes individual understanding
- Each team member expected to answer questions on any part of the project
- Assessed on: clarity of explanation, technical depth, response to questions, methodology justification, AI usage awareness
Key Constraints
- AI assist is allowed and encouraged, but must be documented
- All outputs must be public artifacts (GitHub repo + personal website/portfolio)
- Part 2 is team-based (3-4 students) with rotating project lead
- Part 1 (portfolio) is always individual
- Final portfolio serves as the student’s primary career artifact from the program
- Every capstone project must include an “AI Governance & Risk” section
Open Design Questions
- Research Park partnership logistics and timeline
- Faculty advisor assignment model
- Industry mentor pairing (optional enrichment)
Last Updated: February 2026