Advanced Computing and Machine Learning for Physics and Astronomy

1.5 credits · Graduate

An introduction to the concepts and essential tools of advanced computing and machine learning, via hands-on application to diverse areas of physics and astronomy. Topics may include: advanced distributed, concurrent and parallel computing; big data tools and the use of structured and unstructured data; neural networks and machine learning, including supervised and unsupervised systems; data exploration and visualization.