UNC’s one-year STEM MSDS trains data scientists to deploy cloud-native pipelines, generative AI, and causal-inference techniques in domains from fintech to climate analytics. Students spin up Kubernetes clusters in minutes, apply SHAP to unpack black-box models, and practice stakeholder storytelling in the Data-Viz Studio. A required Ethics Sprint challenges cohorts to mitigate algorithmic harms in live projects.
Graph neural-network predicting power-grid failure cascades
Real-time anomaly detection in streaming IoT sensor data
Generative LLM fine-tuned for grant-writing assistance
Causal-impact study of stimulus checks on local spending
Synthetic-data generator improving fraud-detection training sets
Dashboard tracking ESG metrics for SME supply chains
Edge-AI model optimizing irrigation schedules in precision agriculture
Quantum-computing exploration of portfolio optimization
Benchmark dataset and fairness audit for facial-recognition APIs
Policy white paper on data trusts for smart-city governance
Automated MLOps pipeline with drift monitoring and CI/CD
Shiny app visualizing historical redlining and loan approvals
Master end-to-end ML pipelines and ethical insight to drive data-driven impact.
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