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This course is designed to assist graduate students with the research and development of their new work. The weekly format is determined with the students. In class, they show works-in-progress, try out ideas with their colleagues, and discuss issues involved in their creative processes. Though the class meets only once a week, students are expected to spend considerable time each week in active, ongoing creative research; their independent projects will be presented to the public, either formally or informally, by the end of the term.

Graduate Teaching Fellows in Dance are integrated into the dance program as teaching assistants. In consultation with their academic advisors and the dance faculty, MFA candidates develop an assistantship schedule of approximately ten hours weekly; the courses they develop and teach are listed in the curriculum. All Teaching Fellows bring their own professional histories and contribute their own manners of teaching. Outside of listed class times, TBD, the Teaching Fellows will meet to discuss their courses with the designated faculty and with each other.

For students doing work-study or internships, we will focus on three core areas of professionalization. First, each week will journal our work weeks, discussing and sharing our work experiences in a round-table. Second, we will build our professionalization skills, especially networking (in person and on LinkedIn), resume writing, and doing practice interviews. Finally, we will work on writing 5-year plans, to help us figure out where we’d like to be a few years after graduation. More specifically

Together with calculus, linear algebra is one of the foundations of higher-level mathematics and its applications. This is NOT just the algebra you know from high school. There are several perspectives one can take on linear algebra: it is a method for handling large systems of linear equations, it is a theory of linear geometry (including in dimensions larger than three), it is matrix algebra, and it is a theoretical structure that appears throughout mathematics, physics, computer science, and statistics.