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.
Computational NeuroscienceUniversity of Washington
About this Course
Skills you will gain
University of Washington
Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world.
- 5 stars71.41%
- 4 stars22.21%
- 3 stars4.03%
- 2 stars1.59%
- 1 star0.74%
TOP REVIEWS FROM COMPUTATIONAL NEUROSCIENCE
Excellent course! The field of comp neuro was brough to life by the instructors! The exercises really helped in understanding the content.
Pretty good. A bit of mathematical ambiguity and lax notational conventions, but the course content was solid and presented clearly.
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.
interesting instructor and interesting content. Now I know more about the theoretical research related to neuro function and its connection to machine learning now.
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