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Avis et commentaires pour d'étudiants pour Neurosciences computationnelles par Université de Washington

4.6
étoiles
786 évaluations
183 avis

À propos du cours

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....

Meilleurs avis

AG
10 juin 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.

CM
14 juin 2017

This course is an excellent introduction to the field of computational neuroscience, with engaging lectures and interesting assignments that make learning the material easy.

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151 - 175 sur 181 Avis pour Neurosciences computationnelles

par Marek C

9 avr. 2018

Good introduction to the topic. Course quite easy for engineers, may be quite challenging fro non-engineers. I didn't like quizes - they were too easy and were not provoking too much creative thinking. They were also easier than the lecture material.

par Peter K

30 mai 2017

Great course introducing fundamental concepts in computational neuroscience. People with weak mathematical background can master it although from time to time some more clarification could be helpful. Thanks so much for providing this :-)

par Chiang Y

30 juil. 2020

Pretty comprehensive for beginners, the only drawback is that the course doesn't offer organized ppt or notes for review. Writing notes took me lots of unnecessary time so I suggest a more efficient teaching method.

par Diego J V (

20 févr. 2017

This course serves as a nice introduction to the field of computational neuroscience. However, at some points, more than basic knowledge of differential equations and probability & statistics is needed.

par Gustavo S d S

15 nov. 2016

Learnt concepts about Neural Networks, Supervised / Unsupervised / Reinforcement Learning. Covers topics about Information Theory, Statistic and Probability. Matlab / Python assignments.

par Beatriz B

3 août 2019

In my opinion, the course level ought to be intermediate, not beginner. You can take more out of the course if you already have knowledge in this, or related, areas.

par Hui L

25 févr. 2017

interesting instructor and interesting content. Now I know more about the theoretical research related to neuro function and its connection to machine learning now.

par Mark A

13 juil. 2017

A good look at mathematical models focusing mainly at the synapse and neuron level. The math came a little fast and furious for my 30+ years antique math training.

par Anurag M

3 févr. 2019

Starts off great but get rushed 3/4ths into the course. Too much content, too little explanation, but recovers swiftly to end on a high.

Recommended

par Akshay K J

17 août 2017

Overall - A good introductory course. But the last week, reinforcement learning and neural networks, could have involved programming questions.

par Driss A L

2 déc. 2018

As a self-paced student, I like this kind of course. I hope to see a whole specialization in this field with final capstone project. Thanks.

par Pho H

27 déc. 2018

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

par Ricardo C

27 oct. 2020

it delivers what it promisses: a first grasp of computational neurosciences, with a good overview of the fundamental concepts.

par Serena R

31 août 2017

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

par Erik B

25 août 2019

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

par Vanya E

9 juil. 2017

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

par Avinash

23 août 2020

Very interesting course, gained many skills of modelling that i am going to utilise in my research

par Jeff C

14 nov. 2016

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

par Gaugain G

19 déc. 2019

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

par 徐锦辉

1 sept. 2019

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

par Cezary W

27 sept. 2017

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

par Renaldas Z

30 juin 2017

Great course, if a little bit outdated today.

par Huzi C

14 févr. 2017

Great course and really helpful for me.

par Abhilash C

18 juin 2020

I like professor Rao's commentary.

par ­배용희(대학원/일반대학원 물

29 févr. 2020

Best for the beginner.