This course is one of three courses where students learn the responsibilities and processes of preparing for a live theatrical production by working on an actual production running crew. It requires each student to put in scheduled hours on a particular show. Students will be contributing to a production team (stage manager, assistant stage manager, designer, video/sound technician, etc.) or helping on a run crew (deck hand, wardrobe supervisor, light board operator, sound board operator, dresser, make-up assistant, etc).

This course is one of three courses where students learn the responsibilities and processes of preparing for a live theatrical production by working on an actual production running crew. It requires each student to put in scheduled hours on a particular show. Students will be contributing to a production team (stage manager, assistant stage manager, designer, video/sound technician, etc.) or helping on a run crew (deck hand, wardrobe supervisor, light board operator, sound board operator, dresser, make-up assistant, etc).

Not available at this time

Introductory jazz technique, including body isolations, syncopation, specific jazz dance traditions, and movement analysis. Emphasis on musical rhythmic phrasing, efficient alignment, performance clarity, and performance style. Also taught at Smith.

"Beginning-Intermediate" study of the principles and vocabularies of classical ballet. Emphasis on correct alignment, whole body movement, musicality, and embodiment of performance style. Pointe work included as appropriate. Students must have a solid basic training and knowledge of ballet vocabulary. Also taught at Mount Holyoke and Smith.

Introductory study of modern dance techniques. Topics include kinesthetic perception, efficient alignment, strength, flexibility, movement qualities, exploring new vocabularies and phrasing styles, and individual embodiment of movement material. Also taught at Hampshire, Mount Holyoke, and Smith.

With the recent explosion in availability of digitized text, social scientists increasingly are turning to computational tools for the analysis of text as data. In this course, students will first learn how to convert text to formats suitable for analysis. From there, the course will introduce and proceed through tutorials on a variety of natural language processing approaches to the treatment of text-as-data.

This course will provide an overview of machine learning (ML) with special attention to applications for social and behavioral analytics. Machine learning combines insights from artificial intelligence, probability theory, statistical inference, and information theory to help automate tasks involving pattern recognition, prediction, and classification. "Learning" is analogous to "inference" in statistics and, in fact, the modern statistical toolkit includes various machine learning methods developed to handle large (and messy) datasets.