This page contains homework assignments and demonstration code, all in the form of Jupyter notebooks, from the course Analysis of Neural Data at the University of Oregon (Spring 2023).
The first homework assignment is a general tutorial introducing Python, with an emphasis on numerical computing with Numpy. This is meant to be useful for anyone who is interested in using Python for technical computing, without assuming any prior knowledge of coding or any particular interest in neuroscience.
The other notebooks illustrate concepts from statistics, applying these to the analysis of synthetic data, as well as datasets from real neuroscience experiments in mice, borrowed from the Neuromatch Academy 2020 online summer school for computational neuroscience. Some of the notebooks refer to relevant sections of Analysis of Neural Data by Kass, Eden, and Brown, which was the textbook for the course.
Feedback pointing out mistakes or suggestions for improvements would be very welcome.