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
- 5 stars71.17%
- 4 stars22.62%
- 3 stars3.92%
- 2 stars1.54%
- 1 star0.72%
TOP REVIEWS FROM COMPUTATIONAL NEUROSCIENCE
Very challenging course with fascinating new content that refers to a lot of research in the area! Good start for someone considering computational neuroscience.
Its an amazing course. You will love the way they teach. I'm so glad to get guidance under Prof . Rajesh through this course. One word "Its great".
Excellent course, very clearly and well explained, suitable for beginners. Also, Rajesh's sense of humor makes the course very enjoyable :) Highly recommended!
A well curated course on an equally interesting topic! I've caught an interest for Computational Neuroscience after this experience.
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