UNC’s MS-STDS combines measure-theoretic probability with cloud-native ML. Students implement probabilistic programming in PyMC, architect Spark pipelines, and audit algorithmic fairness in hiring data. Consulting practicums solve live problems from biotech, fintech, and climate-risk startups.
Bayesian hierarchical model forecasting hurricane damage costs
Causal-forest analysis of student-loan forgiveness on credit scores
Spark ETL pipeline for terabyte-scale genomics joins
Shiny app visualizing sports betting odds and Kelly criteria
Differential-privacy synthetic data generator for census microdata
Edge-deployable time-series model predicting solar-farm output
Meta-analysis of publication bias using p-curve diagnostics
White paper on stop-gap metrics for LLM toxicity monitoring
Graphical model detecting money-laundering in crypto flows
Explainable AI dashboard for mortgage-approval decisions
Grant proposal for big-data fellowships targeting rural students
TensorFlow Probability tutorial on Hamiltonian Monte Carlo
Citizen-science workshop teaching bootstrapping via Google Sheets
VR classroom module animating sampling distributions
Open-source R package for robust regression with heavy-tailed errors
Hackathon building dashboards for UN SDG indicator tracking
Survey experiment on visualization literacy and risk perception
Policy brief on algorithmic audit mandates for public agencies
Podcast highlighting statisticians behind COVID dashboards
Infographic comparing model drift detection techniques
Master theory, cloud, and ethics to lead in the data-driven age.
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