Northwestern’s professional MSDS blends computer-science rigor with domain-specific practicums in health, finance, media, and social impact. Students master distributed computing on Spark, deep-learning on GPUs, and causal inference, while an ethics spine interrogates algorithmic justice and privacy. Capstones with partners like Nielsen, Mayo Clinic, and the City of Chicago yield deployable pipelines and policy briefs that shape real-world decisions.
Predict ER patient triage levels with gradient-boosting and calibration plots
Design a recommendation system balancing serendipity and revenue for streaming media
Model wildfire risk integrating satellite imagery and climate forecasts on Google Earth Engine
Develop interpretable churn models for micro-lending platforms in emerging markets
Create an automated feature-engineering library for time-series sensor data
Audit gender bias in resume-screening transformers and propose mitigation layers
Visualize city budget allocations with open-data dashboards enabling resident feedback
Optimize drone-delivery flight paths under weather uncertainty using reinforcement learning
Build a synthetic-data generator preserving statistical fidelity for healthcare datasets
Deploy edge-AI waste-sorting cameras and quantify landfill diversion impacts
Analyze real-time sentiment of esports chat streams for sponsorship valuation
Produce a causal-impact study of universal basic-income pilots on local spending
Construct a knowledge graph linking clinical trials to molecular pathways
Design a geospatial clustering tool locating EV-charging deserts in metro areas
Draft a data-governance framework aligning with forthcoming US privacy legislation
Transform data into responsible, high-value insights with Northwestern MSDS.
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