University of London, Queen Mary

Naturalism seems to be the theater that all fashionable modern theatre people love to hate. This course reconnects with the original dynamic energy of naturalist theater, and to trace a century-long fascination with the art of making it look and feel real. Students look  at new discoveries and explorations of 19th-century science, and at radical moves in painting and literature, as a way of framing our exploration of naturalist drama itself. Students find out why it was so offensive to see a version of their own living room on stage and how theater started to bring all the sordid realities of everyday life on stage. Seminars involve extensive study of naturalist plays, from Ibsen and Strindberg, via Franz Xavier Kroetz to Richard Maxwell, film screenings, and critical and historical texts that place the phenomenon of naturalism in historical and aesthetic context.

This is a practical course that introduces the concepts of machine learning and application of algorithms to several types of available data samples.  Students are introduced to the Python programming language and key concepts related to the TensorFlow (TM) programming toolkit from Google. Programming skills are developed during this course to explore the potential benefits of deep learning algorithms. Students learn how to use scientific computing methods to handle, cleanse, transform, and validate data with the purpose of gaining insights from a wide range of datasets; how to present available data using charts, graphs, tables and more sophisticated visualization tools; how to model data and perform statistical analysis and ad hoc queries; and how to report on key findings and how to summarize and communicate results to mixed audiences.