Neural Networks OpenCourseWare: A Free MIT Graduate Study Class on Neural Networks

Published May 19, 2009

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This course looks at neural learning and computation by investigating synaptic connectivity organization. 'Introduction to Neural Networks,' is a free OpenCourseWare offered by the Massachusetts Institute of Technology (MIT). The original MIT course was part of a graduate degree program in the Brain and Cognitive Science Department.

Introduction to Neural Networks: Course Specifics

Degree Level Free Audio Video Downloads
Graduate Yes No No Yes

Lectures/Notes Study Materials Tests/Quizzes
Yes Yes No

Introduction to Neural Networks: Course Description

Synaptic connectivity is explored in the free MIT OpenCourseWare, 'Introduction to Neural Networks.' Professor Sebastian Seung taught this course that centers on topics that include Hebbian learning, backpropagation, perception models and motor control. Basic mathematical concepts are used to understand response in neural networks. Additional topics discussed include neural development and memory. Frequent feedback loops that dominate brain connectivity are also covered. The original MIT course was a brain and cognitive science master's program elective choice.

This free OpenCourseWare includes a brief course reading list, class lecture notes, sample classroom assignments and downloadable study materials. To view these varied course materials, visit the neuroscience course page.

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