Explanation
Computational Neuroscience is a comprehensive course that teaches an introduction to basic computational methods for understanding what neural systems do and determining how they work. We will examine the computational principles that govern various aspects of vision, sensory control, learning, and memory. Specific topics that will be covered include information representation by neural networks, information processing in neural networks, and algorithms for adaptation and learning. We will use Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of the concepts and methods presented in the course.
What you will learn in this course:
- computational neuroscience
- Artificial Neural Networks
- reinforcing learning
- Model of biological neurons
Who is this course for:
- This course is primarily intended for third or fourth year undergraduate and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.
Course specifications:
- Publisher: Course
- Teachers: Rajesh PN Rao , Adrienne Fairhall
- Language : English
- Level: Beginner
- Number of chapters: 8
- Course duration: up to 26 hours
- Format: mp4
- Giving institution/university: University of Washington
The course includes:
Requirements:
- There are no prerequisites for this course
Images of Computational Neuroscience
Example clip:
Installation guide:
After the production, you can watch the course in your favorite video.
Subtitle: English
Quality: 720p
Download links:
Password: free download software
File size:
2.21 GB