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Learner Reviews & Feedback for Computational Neuroscience by University of Washington

4.6
stars
945 ratings

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 7, 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 10, 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 - 175 of 224 Reviews for Computational Neuroscience

By Fatma T

Jan 12, 2021

very informative, thank you

By Shawn C

Feb 5, 2021

Compact and Comprehensive.

By Yi-Yin H

Jun 29, 2019

It was an amazing journey!

By Wambui K

Dec 23, 2018

Great learning experience

By Aditya V

Dec 12, 2017

loved it ...learned alot

By Vili V

Jul 28, 2019

Very enjoyable course!

By 刘仕琪

Mar 11, 2017

The teacher is funny!

By Cian M

Oct 6, 2019

Very nice indeed!

By Gavin J J

Sep 11, 2017

Its an eye opener

By RAMAN S

Sep 27, 2020

Excellent course

By Palis P

Jun 14, 2020

Just amazing! :)

By Bilal C

Apr 12, 2017

I recommend it

By Mtakuja L

Apr 3, 2017

Nice course !

By Ekin K

May 16, 2021

great course

By KUNXUN Q

Apr 28, 2017

very helpful

By Sourabh J

Nov 5, 2016

Good course!

By Jacob D

Oct 20, 2020

This topic combines a lot of what I find interesting so I am grateful this course exists. Before I started it, my hope was to walk away with more familiarity and a solid foundation for computational neuroscience. As far as I can tell, I was in fact able to gain a basic understanding. There were also a lot of really fascinating concepts throughout the course.

My only issue is that some ideas (probabilities and encoding for instance) gave me a lot of trouble and I felt like instructor couldn't explain these things in a way that I could understand. Sometimes they'd just toss a bunch of unnecessary big words and equations or invoke strange conventions that I'm not comfortable with, leaving me struggling behind. To be fair, there were many ideas for which the instructor also gave very helpful examples or made intuitive connections with other ideas. I wish I could elaborate better on the teaching quality, but this is only a review.

Overall, I was exposed to many new interesting concepts. I seriously hope that I might be able to work in a field similar to this one day.

By claudio g

May 22, 2018

I have really liked this course,but there is a lot of statistics I didn't expect to find at the beginning. Ihave given me exactly the flavor of what Computational Neuroscience is and what are the field of applications, which are REALLY interesting. Honestly I have found a bit too condensed the part regarding the description of "cause" and all the related statistic stuff which I think should deserve some 1 or 2 videos with solved problems. All summed up, I think this course is really worth of taking. Best regards to the professors and to the mentors and to those who have given me a lot of help with their posting on the forum. Their doubts and the relative answers have really been enlightening for driving me towards a better understanding of the matter. Thank you to all of you.

By Andrey G

May 25, 2022

Курс очень интересный. Лекции профессора Рао доставляют истинное наслаждение любознательным зрителям. Выверенная подача сложного материала. Простые, но ухватывающие суть, примеры. Четкое произношение. Мягкая ирония. Также было очень интересно слушать дополнительные лекции по математике. Хотя материал мне был знаком, но я был восхищен как лектор его преподносит. Интересные тесты. Однако есть недостаток: редко какую лекцию можно было посмотреть от начала и до конца без того, чтобы не зависнуть. Ждать несколько часов, чтобы подгрузилось видео, без всякой гарантии на успех - это не для слабохарактерных. В остальном, желаю всяческих успехов коллективу профессора Рао.

By Shreyas G

Jul 18, 2020

The course provides a really good insight into the field of computational neuroscience, touching every area possible. The experiments and real-life research work discussed throughout gives a good understanding and exposure to the field. Assignments equip the student well with the necessary skills and thought process in problem-solving while strengthening the concepts as well. However, I found the computational knowledge required for the course demanding. Though there was adequate help available, more could've been helpful, especially in python. It was a great learning experience.

By Aditya A

Mar 28, 2019

I liked the course. I enjoyed solving the problems and I am now confident in learning more advanced concepts and getting my hands dirty in neural networks and machine learning.

I only have one complaint like suggestion, if only the TAs or the instructors could show some examples of solutions or algorithms for the concepts, it would have been much easier. Although, i have understood the concepts, I have not yet grasped the implementations of the concepts in actual codes and programs. Please update the course regarding that. Thanks a lot again to Rajesh, Adrienne and Richard.

By Ali A M

Aug 17, 2022

T​he material is superb. I loved how the course progressed and the way they described the theory behind concepts such as STA.

I​ loved the guest lectures and talks that gave me an idea of what it is like to work in the field of computational neuroscience and since I am planning on continuing in this major, it a thrilling adventure for me.

O​ne thing I think should be improved is the clearity of questions in the quizes. S​ome questions in the weekly quizes can be unclear an need further discussion.

I​n the end, thank you very much for this wonderful experience.

By Moustapha M A

May 26, 2018

The course over all was very good but I didnt given it five because of the following : in course 2-5 the lectures were not coherent and the there was no expalantion for how certain experiments or measurments were done and hence natural progression to associate the mathematics. The lecturer tends to speak fast and sometimes eat her words so there was absence of clarity . The lectures were not well structured . on the otherhand lectures 6-8 were much clearer in presenation and scope and more linked with the quizes.

By Steven P

Nov 13, 2019

Really interesting overview of the concepts, math and coding necessary to understand how neurons work. The lectures are hit and miss when it comes to explaining the content, a majority of the lectures focused on derivatives and mathematical concepts which lost me. The supplementary videos, especially with Rich were really valuable and helped to synthesize some of the content. Felt like there was a ton of information packed into this course, just not all completely applicable.

By Wilder R

Jun 28, 2017

I loved the course and the way Professors Rajesh and Adrienne conducted it. I only think the slides and lecture notes could have some more material. I'm a Software Engineer, with a background in Computer Science, but I have been far from math for quite some time (that's why I'm now doing a Cauculus 1 course). I got lost a few times in the quizzes due to lack of information.

But I loved the course and all the new knowledge I acquired. I will certainly recommend. it.