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Learner Reviews & Feedback for Computational Neuroscience by University of Washington

4.6
stars
1,052 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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51 - 75 of 250 Reviews for Computational Neuroscience

By Lucas S S

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Jul 28, 2017

Well-paced, great lectures and good supporting material to follow up with the studies. Totally recommend to people that are interested in modeling the brain (be it neurons or synapses or behavior) with theoretical and computational tools (even if you do not master the math/programming)

By Denis L

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Jun 8, 2021

an excellent course for machine learning specialists who are interested in the nature-based principles of computing systems. unfortunately, the course does not have may examples of solving practical problems related to writing code, designing network architectures, usiing spikes etc.

By Gianluca G

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Jun 30, 2020

I am stunned by the amount of info and knowledge I acquired with this course. It really opens up your mind about how your brain works and how you analyze the external world. Totally suggested for beginners (with a good math background) and for who just wants to learn cool stuff

By Ravinder S

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Jul 25, 2017

Loved this course and will give me direction in grad school however a lot of the information still ending up being over my head, even after watching supplementary videos. This may be a fault of my own instead of a fault of the class. Really enjoyed the first/last teacher.

By Sezan M

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Mar 12, 2021

This course is very fun and interesting . It is a perfect introduction to Computational Neuroscience which also encourages you to go further in this area. I totally recommend if you are interested in the field and looking for a starting point. This course must be it.

By Kruppa A S

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May 28, 2020

Thank you and your team for adventurous journey through such interesting cross-science subject! Especial respect to Richard Pang, who is making complicated things simple!

Namaste and good luck in your further investigation!

With big warm feelings, hasta la vista! :)

By Tucker K

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Mar 11, 2018

Very interesting and well taught course. I came in with a background in CS and some ML and very little experience with neuroscience and felt like I learned a good bit about neuro and developed a more solid understanding of the principles underlying ML techniques.

By Mingchen Y

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Mar 3, 2019

This course is very helpful! I especially enjoy doing the exercise which is well designed and facilitates my understanding of CN. Besides, I find the textbook Theoretical Neuroscience by Dayan and Abbott more understandable after I finished this coursera course.

By Paulo V C

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Apr 26, 2021

Excelente curso! Diversos aprendizados, desde a fisiologia e cognição do sistema nervoso à probabilidades, tomadas de decisões, programação, dentre outros. Recomendo um estudo prévio sobre esses assuntos, com enfoque na parte de probabilidade e estatística.

By Kanchana R

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Jan 29, 2017

Very informative. I started the course as I am an undergraduate who is involved in a research and development project on Spike Timing Dependent Plasticity. This course opened me into the literature on STDP and helped me understand the relevant material.

By Ulaanbulag T

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Aug 2, 2017

With a extremely rich content, this course is a challenge for students, even for those with maths, ML or neuroscience background. The course requires students to master knowledge of these three fields, but it will prove that it DESERVES the efforts.

By Peter G

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Nov 17, 2016

Great course, but it requires quite a bit of mathematics/physics to get through. Enough material in there for three or four courses. The quizzes are not hard though - in fact I'd preferred it if the programming exercises had been more challenging.

By Dadarkforce

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Apr 7, 2019

This course was enjoyable, to say the least. It helped explained the thinking behind the conceptualization of existing algorithms that I've been introduced to in other courses for AI, but it further explained how they were mathematically derived.

By Tom R

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Apr 23, 2017

Really great course to supplement reading of Dayan and Abbott's Theoretical Neuroscience text. Programming assignments were really helpful in getting practical understanding of concepts. Only wish there were more graded programming assignments!

By Marcos A

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Dec 18, 2016

Excellent Course, with very clear and detailed explanations, and a lot of additional materials indicated through links and papers. I particularly enjoyed the Guest Lectures as well, showing the applicability of what was learned in real life.

By Yuyan Z

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Oct 30, 2019

A very good introduction to computational neuroscience! The course demands a relatively high level of mathematics (such as linear algebra, optimization problems, etc.), but all of them are quite clearly explained in the lectures.

By Estelle B

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Feb 7, 2020

Very interesting topic. I particularly liked the tests with programming exercices. It helped to apply the concepts I learned quite well. The tests overall are good quality and do not only expect student to copy/paste knowledge.

By Felipe S

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Dec 1, 2022

A course that presented knowledge at certain advanced moments, demanding more time and understanding from the student. Congratulations to the instructor-coordinators and guest speakers, as well as the exciting Rich Pang.

By Shashank B

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Dec 6, 2018

Very clear explanations by professors. I really liked the design of the class and the lectures are very easy to understand if you are just starting in Neuroscience (they don't throw around complicated jargon)

By Nikolaos P

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Jul 29, 2019

Perfect course. The only feedback I would give is, if possible, to include slides in the weekly material for review instead of just text. Thank you for this amazing tour through Computational Neuroscience!

By André M

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Jun 18, 2020

Fantastic introduction to the field. Very engaging lessons, good pace where new concepts are introduced regularly enough. Makes me want to go back, there's a lot of things I'd like to get a refresh on.

By Jaime R

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Apr 8, 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

By Adam G

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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.

By Kai S

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Oct 25, 2021

A wonderful rather lightweight introduction to the field with much enthusiasm, some good examples and code snippets, and a great team. Thank you for the adventure ride!

By Taiping Z

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Nov 16, 2016

It is an excellent overview course of computational neuroscience and a wonderful introduction for beginners who want to join in computational neuroscience research.