USC’s Applied Data Science MS tears down silos between algorithms and action. Learners containerize micro-models with Kubeflow Pipelines, build Neo4j knowledge graphs for cinematic IP, and deploy Federated-Learning pilots on hospital edge nodes under HIPAA. Rotating sprints pair teams with sports, fintech and climate faculty; an Ethics spine hardens LLM red-teaming drills. By graduation, students have shipped, monitored and mitigated models at scale.
CI/CD pipeline auto-retraining wildfire spread model
Knowledge-graph recsys for streaming platform content
Homomorphic-encrypted analytics on bank fraud data
RL traffic-signal optimization with SUMO simulator
Model interpretability dashboard using Captum + React
Synthetic tabular data generator under δ-DP budgets
Git-based data version control demo with DVC
GAN up-scaler for satellite imagery of crop health
Edge AI model classifying trash vs. recycling on camera
Policy brief on AI model export controls
Graph anomaly detector flagging money-laundering rings
Shapley value feature store audit for fairness
Real-time lakehouse pipeline on Delta + Spark
LSTM energy-load forecast pushing to smart grid
LangChain agent automating literature review synthesis
Engineer trustworthy models that move seamlessly from notebook to production.
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