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Skills related

behavioral neuroscience
cognitive neuroscience
computational logic
computational physics
computational neuroscience

People often say

Helpful Guide, Beginner Friendly

8.08%

Clear and Concise Explanations

8.07%

Good and logic Introduction

7.79%

Applied fundamentals and worthy instructor

6.84%

Effective Training Methods

5.58%

Overview

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 focused on third- or fourth-year undergraduate students and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.

Syllabus

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Introduction & Basic Neurobiology (Rajesh Rao)

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What do Neurons Encode? Neural Encoding Models (Adrienne Fairhall)

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Extracting Information from Neurons: Neural Decoding (Adrienne Fairhall)

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Students appreciate this online course as an excellent overview of computational neuroscience and a wonderful introduction for beginners interested in joining computational neuroscience research.

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Free

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SkillMapper rating:

95%

Start date:

Self-Paced

Amount of students:

104.0K

Duration:

27 hours

Downloadable resources:

64

Certificate of completion:

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