Modeling, Mining and Machine Learning in Astronomy

Catalog description

This course covers probability, statistics, and signal processing to develop algorithms for detecting objects and events in astronomical data. Topics include frequentist and Bayesian model inference, time-series analysis, clustering, classification, genetic algorithms, Markov Chain Monte Carlo, and neural networks. Students will apply these methods to real and simulated data using Python and Jupiter notebooks.