The Sports Analytics Certificate bridges academic training and professional practice through four strategically sequenced courses. You’ll build machine learning foundations, master R programming and visualization, engage with industry decision-makers, and complete a public-facing capstone project.
What Makes Us Different
- Student-First Education: Courses are tailored to bring all students to the same level of excellence
- Integrated Capstone Design: MTH 803 and STT 834 run together, giving you months (not weeks) to develop meaningful projects
- GitHub-First Approach: Your project website becomes your portfolio, not just a course deliverable
- Practitioner-Driven Learning: Weekly standups mirror industry workflow; guest speakers share real implementation challenges
- AI Partnership Skills: Explicit guidance on using AI tools responsibly—debugging, exploring approaches, and maintaining understanding
Program Format
- 100% online, synchronous
- Certificate completion: 8 months (minimum duration)
- Small cohorts (6-13 students) enable meaningful collaboration
MTH 801
Machine Learning Algorithms
Fall
Mathematical foundations of ML methods—regression, PCA, SVMs, and neural networks—applied to sports questions in R.
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Statistical Learning and Data Mining
Fall
R programming, statistical modeling, and publication-quality data visualization using real sports datasets.
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Sports Analytics Practicum
Spring
Weekly conversations with industry professionals from teams, leagues, agencies, and sports media.
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Sports Analytics Capstone
Spring
Scope, execute, and present a portfolio-quality analytics project with a public GitHub Pages website.
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