SciPy 2016

Video recording and production done by Enthought

Jupyter notebooks and the Python ecosystem provide a unique opportunity for interactive, web-based, teaching of content that has not traditionally leveraged scientific computing resources. We discuss the design and implementation of a new biological signal processing course at Harvard, ES155, which fuses Wearable technology and cloud-based analysis of data. ES155 bridges the gap that has traditionally existed between Electrical Engineering and Computer Science education, in a framework that we term “Labs in the Wild”. In the process of designing the course, we have had to solve the problem of serving Jupyter notebooks on the cloud reliably using AWS EC2 instances. This is a challenging problem because a successful approach must be scalable, cost-effective, reliable, and address the privacy concerns associated with cloud-based technologies. We describe our system in this talk, and perform a live demo of how students in our class interact with the system, and give examples of ingenious final projects put together by students. Being cloud-based, our system lowers the barrier of entry for students to begin using Python for scientific computing.

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