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Learner Reviews & Feedback for Computational Neuroscience by University of Washington

4.7
stars
700 ratings
167 reviews

About the Course

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....

Top reviews

JR

Apr 08, 2018

Extremely enlightening course on how Neuron's work and the science of computational neuroscience. Even if you don't want to get into the complex mathematics you can get a lot out of the course

AG

Jun 11, 2020

Brilliant course. For a HS student the math was challenging, but the quizzes and assignments were perfect. The tutorials and supplementary materials are super helpful. All in all, I loved it.

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151 - 167 of 167 Reviews for Computational Neuroscience

By Pho H

Dec 28, 2018

Pretty good. A bit of mathematical ambiguity and lax notational conventions, but the course content was solid and presented clearly.

By Serena R

Aug 31, 2017

I found this course helpful and inspiring for my research activity. I suggest it to anyone who has basic mathematical skills.

By Erik B

Aug 25, 2019

Overall I enjoyed this class, but towards the end it gets more into machine learning and away from the neuroscience.

By Vanya E

Jul 09, 2017

Great overview of a really cool field, gives nice intuitions for ideas in computational neuroscience.

By Jeff C

Nov 14, 2016

In general very good, but some concepts are rushed over due to the short length of the course.

By Gaugain G

Dec 19, 2019

Très bon cours je recommande pour tous les gens intéressé par les neurosciences théoriques

By 徐锦辉

Sep 01, 2019

A better tittle for this course is 'From neuroscience to artificial intelligence'.

By Cezary W

Sep 27, 2017

Quite interesting. I would see more explanation of some phenomena, though.

By Renaldas Z

Jun 30, 2017

Great course, if a little bit outdated today.

By Huzi C

Feb 14, 2017

Great course and really helpful for me.

By Abhilash C

Jun 18, 2020

I like professor Rao's commentary.

By Yonghee B

Feb 29, 2020

Best for the beginner.

By Christopher L M

Jun 03, 2017

[3.5 stars] The course provides an overview of some interesting topics. I would have prefer more emphasis on applications, perhaps in the form of additional exercises. Overall, I have my adventure hat on and I am excited to push on further into the neuro-jungle.

By Renjith B

Feb 20, 2018

I just started the course. But it is exciting for me as a Machine learning and deep learning practitioner!!!

After week 1, the learning curve is steep. The topics are exciting but lectures are not engaging.

By Sami J

Jan 27, 2020

Very interesting, buy also pretty superficial. Surprisingly low amount of hands-on computation considering that it's a class in computational neuroscience.

By Caesar H

May 28, 2020

Overall, this course was very interesting and the organization made sense. However, if you are looking for a deep understanding of computational neuroscience as a computational novice, this course is much more advanced than they make it seem in the overview and it will not help. Conceptually, I feel I learned a lot, but practically, I still have no idea how to implement solutions. It is a must (not a bonus) to know MATLAB or Python coding. It is a must (not a bonus) to know calculus (definitely derivations, integrations, and limits in detail). The TA videos were one of the best parts of the course, but there is very little to no support if you are stuck with questions (the forums were not very helpful; get yourself a tutor in real-time). The biggest issue I have with this course is the lack of practice problems. I would suggest that at the end of each lesson, a few practice problems are given with full solution explanations. Then, a set of a couple of practice problems should be given to solve (with detailed solutions at the completion of the homework). Not until this practice and training are implemented should there be a quiz. The quizzes were the worst part of the course. They happen at the end of each week's lessons, and there are no real explanations for each solution. The forum isn't very helpful because it's a quiz, and they don't want to give out answers (understandably so). Therefore, a practice set should happen after each lesson but before taking the quiz.

By Mathew K

Jun 04, 2020

The course started out quite well, but increasingly became very difficult to follow. Instruction during the second week through the fifth week was particularly difficult for me to understand. Only the additional lectures by Rich made sense, but didn't go deep enough to help me understand the course material.