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Nov 23, 2024
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NEUR 182 SC - Network Science and Machine Learning Using Neural Signals
This course teaches students the theory and practice of computational analyses of neural networks and neural classification. We will use real neural signals (e.g., spikes, EEG data, fMRI data, diffusion MRI data) in Python, Matlab, and R, so some computer programming experience is required (e.g., BIOL133, PHYS108, PSYC123L, or equivalent). In this course, students will learn how to identify and analyze neural networks and how those systems relate to information processing, conceptual classification, and decision-making. Each class will involve theory and practical applications, giving students conceptual and computational capabilities that they can use for their own scholarly inquiry.
Prerequisite(s): NEUR095L JT or equivalent AND (BIOL133L KS , PHYS108 KS , PSYC123L SC , or equivalent)
Course Credit: 1.0
Offered: Annually
Please refer to the course schedule on the Scripps Portal for current course offerings and details.
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