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Learner Reviews & Feedback for Computational Neuroscience by University of Washington
1,065 ratings
About the Course
This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.
Top reviews
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This is a wonderful start for a biologist , to get idea of concepts of learning . An advanced course focused more on brain circuitry is suggested.
Thanks a lot
DL
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As a self-paced student, I like this kind of course. I hope to see a whole specialization in this field with final capstone project. Thanks.
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251 - 254 of 254 Reviews for Computational Neuroscience
By SINA M
•Jan 3, 2023
Materials are complex and this course maybe just brushes over it
By Tanvi P
•Jul 13, 2020
The course is good but requires excellent math and programming skills. Students who don't like math might face some difficulties.
By Chris c
•Oct 19, 2022
Difficulty increases too quickly. The TA had the only good lectrues.
By Mohammad P
•Sep 12, 2023
that wasnt what i think