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

4.6
étoiles
773 évaluations
181 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

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.

JB

May 25, 2019

I really enjoyed this course and think that there was a good variety of material that allowed people of many different backgrounds to take at least one thing away from this.

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151 - 175 sur 179 Avis pour Neurosciences computationnelles

par Peter K

May 30, 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

Jul 30, 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 (

Feb 20, 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

Nov 15, 2016

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

par Beatriz B

Aug 03, 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

Feb 26, 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

Jul 13, 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

Feb 03, 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

Aug 17, 2017

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

par Driss A L

Dec 02, 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

Dec 28, 2018

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

par 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.

par 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.

par Vanya E

Jul 09, 2017

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

par Avinash

Aug 23, 2020

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

par Jeff C

Nov 14, 2016

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

par Gaugain G

Dec 19, 2019

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

par 徐锦辉

Sep 01, 2019

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

par Cezary W

Sep 27, 2017

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

par Renaldas Z

Jun 30, 2017

Great course, if a little bit outdated today.

par Huzi C

Feb 14, 2017

Great course and really helpful for me.

par Abhilash C

Jun 18, 2020

I like professor Rao's commentary.

par ­배용희(대학원/일반대학원 물

Feb 29, 2020

Best for the beginner.

par Christopher 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.

par 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.