I always have side interest in neuroscience. So here's just a note to myself, I am taking Coursera's Computational Neuroscience for fun. This is the second time I loop through the course with more understanding on neural networks, and it feels like a completely different class. The others are just my casual interest - one day I will go through them one by one.
Just a disclaimer: unlike my Top-5 List in deep learning, I only have amateurish understanding of computer neuroscience. I also only cursory experience of each of these classes. This might change when I finish a significant portion of them (definition: 50%+). But for now, caveat emptor!
- UW's Computational Neuroscience (See my impression here.)
- Synapses Neuron and Brain from Coursera (See my impression here.)
- edX's Neuronal Dynamics, the harder version used by grad students: Neural Network and Biological Modeling
- Harvard's Fundamental of Neuroscience
- EdX's Cellular Mechanism of the Brain
- Coursera's Understanding Neurobiology
- Neuronal Basis of Consciousness from Caltech
- PU's Advanced Neurobiology I
- PU's Advanced Neurobiology II
- HBP's Neurobiology Lectures
Measurement and BCI
- Coursera's Functional fMRI,
- Neurohacking in R
- Duke's Medical Neuroscience
- Human Brain Project's Courses on Brain Medicine
- Coursera's Drug and Brain
- Introduction to Clinical Neurology
Other Biophysics/Biomedical Engineering-Related
Other Interesting Sources of Information: OpenCulture.
(Edit at 20170524) Categorize almost all classes into sub-categories. Not entirely sure I am right. But on the computational neuroscience ("theoretical") side, things look clear enough.
(Edit at 20170522) Finished UW's Comp N. Sci. Changed the ranking so that Synapses, Neuron and Brain got a higher ranking.
(Edit at 20170501) Made another 4 classes under the category of "Neurobiology".
(Edit at 20170427) Create 5 classes which under the umbrella of "Computational Neuroscience". For the most part they are more quantitative than the other classes.