University of California, Berkeley 4 credits Engineering
This course introduces engineering students to elements of statistics and probability, followed by a module-based introduction to select computational techniques from data science and stochastic optimization. Each module is based on a contemporary engineering problem of broad interest. The computational techniques presented in the course are drawn from Bayesian optimization, supervised learning, neural networks, classification, and Kalman filtering.
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