Raquel Prado

Raquel Prado is Professor of Statistics in the Jack Baskin School of Engineering at the University of California, Santa Cruz, where she has been faculty since 2001. She holds a PhD in Statistics and Decision Sciences from Duke University. She is a Fellow of the American Statistical Association (ASA) and the International Society for Bayesian Analysis (ISBA). Her research interests include the development and implementation of modeling, inference and prediction tools for data with temporal and spatio-temporal structure, with a focus on the analysis of non-stationary and large-dimensional biomedical signals and neuroimaging data. Her published research includes the book "Time Series: Modeling, Computation, and Inference'" (second edition co-authored with Marco Ferreira and Mike West), as well as a variety of papers.

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Bayesian Statistics: Time Series Analysis (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Time Series Analysis (Coursera)

Dive into the world of Bayesian statistics with our specialized course on Time Series Analysis. This is the fourth in a sequence designed to equip you with a deep understanding of Bayesian methods, focusing specifically on analyzing patterns over time. Whether you're a seasoned data scientist or just starting out, this course will enhance your ability to model and forecast temporal data effectively.

Jun 29th 2026
5-12 Weeks
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