Computational Physics Seminar

Introduction to Python coding and its application to data collection, analysis, and statistical inference. The course consists of weekly hands-on labs to introduce students to developing in the Jupyter environment. Key concepts include understanding random errors, treating data as functions of frequency, and effective visual communication. Data for labs is drawn from a variety of sensors and sources including simulations, accelerometers, astrophysics, and Art Museum paintings.