UC Data Science combines rigorous statistics with scalable computing. Students build end-to-end pipelines, contribute to open-source libraries, and win Kaggle competitions.
AutoML pipeline predicting wildfire spread from weather and fuel data
Bias audit of facial-recognition algorithms across skin-tone spectra
Interactive dashboard forecasting hospital ICU capacity
Graph neural network detecting fraud in blockchain transactions
Policy memo on algorithmic transparency standards for city services
Federated-learning model for wearable health-tracker anomaly detection
Text-generation analysis of GPT detectors vs. human raters
Satellite-imagery segmentation of urban green spaces and cooling effects
Recommender system for personalized climate-action tips
Crowdsourced sentiment map of public transit satisfaction tweets
Workshop teaching indigenous data sovereignty principles
Differential-privacy mechanism balancing utility and confidentiality in census data
Deep-fake audio classifier leveraging wavelet transforms
Data journalism piece on eviction trends during pandemic moratoria
Time-series model of renewable-energy output volatility
Interactive JupyterBook teaching intro stats with real UC datasets
Network analysis of misinformation echo chambers on Telegram
Anomaly detection in smart-grid sensor streams using variational autoencoders
VR visualization of high-dimensional t-SNE embeddings
Ethnography of data-science team workflows in non-profits
Turn data into impact—master analytics and AI with UC Data Science.
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