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Learner Reviews & Feedback for Computational Neuroscience by University of Washington

851 ratings
198 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

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

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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26 - 50 of 196 Reviews for Computational Neuroscience

By Marta M

Mar 11, 2017

It was by far the best course I've taken on Coursera. For someone not dealing with math in their everyday life it could have been a bit challenging, but I really enjoyed watching how math, physics and neuroscience use the same concepts and how various models can be interchangeable.

Main subject was super-interesting, but I also enjoyed how it showcased how mathematical concepts can be used and applied. It's really disappointing that such approach is not that common in formal education many of us have received... For such interesting topics you presented I would go back to university and learned differential equations once again, seeing some purpose in them at last. I always knew that mathematics is a beautiful language, but during my education no-one showed me such profound and exciting problems to express them in it.

The instructors were great and guest lectures were fun as well. I am almost regretting choice of my everyday computer science career when hearing about problems you get to solve :) Thanks a lot! This was definitely one of the best online courses I've seen and time spent on it was not wasted.

By Maxwell G

Mar 16, 2017

I loved this course. It is an excellent introduction to the realm of Computation Neuroscience. The lecturers presented the concepts clearly and effectively. Dr. Rao was especially great. However, those looking to take this course should have some knowledge of Differential Equations, Calculus, Linear Algebra, and either Python or Matlab before taking this course.

I had not taken very much Calculus or Differential Equations prior to taking this course, and I had to do a fair amount of external research to understand some aspects of the lectures.

The professors who teach this course do a great job of explaining the concepts and ideas of the topic, rather than just reading lots of formulas. They break the math down to help the viewer intuitively understand what each one is doing. Someone taking this course who doesn’t not have that solid of a math background will have some trouble, but the course won’t be impossible. A bit of Programming experience with either Python (2 or 3) or Matlab, however is a must.

By Victor G O M

Jul 5, 2020

Very insightful course! It requires a little bit of statistical and calculus base, but nothing that some extra studying can't help. The course is also accompanied by a set of supplementary lectures that are very helpful as well. I recommend for those who are starting the course now to go through the supplementary material before starting the lectures.

The course opened my mind a lot about the computational neuroscience field. I can say without a doubt that this course grew a love for the field inside me, which I will keep studying from the referred books and materials. I hope to get started working on my own projects using what I learned pretty soon.

Thanks for Rajesh and Adrienne for this amazing course!

By Vikrant J

Mar 16, 2019

Computational Neuroscience is a well structured, insightful and methodical course. There were so many moments when I was dumbstruck by the power which our brain has, that I've lost the count of them! As a biophysics, signal processing enthusiast, I'm considering to go for higher studies in the field of Neuroscience and this course has just made my decision unequivocal. Big kudos to the instructors Prof. Rao and Prof. Fairhall for their inputs for both, the content of the course and sharing their research material! I can't wait to explore the brain to its fullest! :D

By Shwetank P

Apr 27, 2019

This course will be one of the most satisfying pursuits for any individual interested in exploring the intersection of neurobiology, AI and Statistics. The course is really well-rounded covering all major portions in the computational neuroscience. The supplementary material provided for exploration is really intriguing and a must go for people interested in understanding the gory details behind the equations. Hands down! this one is the best MOOC experience so far for me.

By Sergey A R

Nov 4, 2016

Te course captures from the very beginning!

The lectures and work with REAL data (despite it's obvious simplicity) will hold you till the end.

The confirmation of the theory, calculated with my own hands, with the practical results from the laboratories.

It's just a first step, the next one is in supplemental materials, and then proceed farther and farther.

Well, and a fly in the ointment :) a lack of programming through the course, we can do more! :)

By Iván E A

Dec 22, 2019

This course is an introduction to the vast field of computational neuroscience. Every week the subject is different. I found the supplementary videos very helpful on their own, explaining concepts like entropy, probability distributions, gradient descent, and more.

I have completed several Coursera courses, and this has the best kind of weekly tests (homework). I enjoyed the coding and felt that It made the concepts clearer.

By Prachi S

Dec 13, 2020

The course provided deep insight into various aspects of brain and how we can use our knowledge of mathematics and physics to understand the biology and mechanism of brain. The assignments helped me to understand the course better and kept me motivated throughout the course. It encouraged me to know in further details about this interesting field of computational neuroscience.

By André M

Nov 20, 2016

Excellent course, looking forwards to going back over the lectures and consolidating what I've learnt. Big word of thanks to Rajesh and Adrienne, but also to TA Rich Pang, who does an excellent job getting you up to speed on the maths. Very excited about what I've learnt in the course and the way it's made me look at neuroscience in a new and richer way.

By Daniel B

Dec 2, 2016

Phenomenal course. My background is in mechanical engineering, but all the biological concepts were explained clearly and concisely. I wish a bit more modeling in Matlab was done, but overall I'm very pleased with the course. A solid background in linear algebra, statistics, and some basic calculus is recommended to get the most out of the course.

By Diego B

Apr 7, 2017

I must admit that, before starting this course, I was skeptic about an online course on Computational Neuroscience. My initial feelings totally reversed during the first weeks of the course. I really appreciated the effort of Rajesh and Adrienne to explain the complex mechanisms of neurons and brain functions in a clear and enjoyable way.

By Julieth L C

Sep 11, 2020

I really liked these course, the mathematical component was very complete like the biological component, my only problem was that there was an exercise that I never could understand at all, I'd like a more clear feedback. However in general I recomend the course, the professors are really good. Thank you.

By Amir Y

Aug 1, 2017

I greatly enjoyed this course. It has a nice structure, and the progress is quite reasonable assuming you have decent background in linear algebra and calculus derivations. They still offer great supplementary resources for those lacking necessary background knowledge. Overall, I'd recommend it.

By AmirHossein E

Mar 26, 2017

This course is an absolute must for those interested in computational neuroscience. The professors are very knowledgeable and the course is very rigorous. The techniques introduced in this course are useful and the supplementary material is enough to last for you months of reading on this topic.

By Deepak R V

Dec 1, 2020

One of the most enjoyable and intriguing course, Prof. Rajesh Rao, Prof.Adrennie fairhall and team, put great efforts and the course is very well executed.

The quizzes are awesome.

A great learning experience

#Brain #Information_Theory #Dynamical_systems #SIgnal Processing #Machine_learning

By Rohit P

Jun 4, 2020

Good work by both the tutors. I really like how simple and easy to understand the course module was here, however i wish that Matlab and Python tutorials were a bit more approachable and so i would suggest other learners to look into and sharpen their Math skills before taking this one!

By Matthew W

Jun 23, 2019

As a beginning PhD student in computational neuroscience, I found this course to be incredibly useful as a refresher. And as an introduction to the subject, it is incredibly engaging, interesting and, of course, one fun adventure! Many thanks to both Rajesh and Adrienne for this course!

By Lucas S S

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 Gianluca G

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

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

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

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

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

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

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.