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Вернуться к Вычислительная нейробиология

Отзывы учащихся о курсе Вычислительная нейробиология от партнера Вашингтонский университет

4.7
звезд
Оценки: 670
Рецензии: 157

О курсе

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....

Лучшие рецензии

JR

Apr 08, 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

CM

Jun 15, 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.

Фильтр по:

101–125 из 155 отзывов о курсе Вычислительная нейробиология

автор: donghyuk k

Feb 06, 2017

please let me show quiz again please

автор: Swarn S ' D A W

Nov 03, 2019

The discussion forums helped a lot.

автор: 谭敬斌

Mar 31, 2020

interesting and inspiring courses

автор: ABDURAHMAN H A

Oct 03, 2016

Superb lectures and explanations

автор: Adam E

May 22, 2017

Comprehensive and challenging.

автор: Efraim

May 20, 2020

This is my talent and passion

автор: Hariharan L

Aug 24, 2019

I find it really interesting

автор: Yi-Yin H

Jun 29, 2019

It was an amazing journey!

автор: Wambui K

Dec 23, 2018

Great learning experience

автор: Aditya V

Dec 12, 2017

loved it ...learned alot

автор: Vili V

Jul 28, 2019

Very enjoyable course!

автор: 刘仕琪

Mar 11, 2017

The teacher is funny!

автор: Cian M M

Oct 06, 2019

Very nice indeed!

автор: Gavin J J

Sep 12, 2017

Its an eye opener

автор: Bilal C

Apr 12, 2017

I recommend it

автор: Mtakuja L

Apr 03, 2017

Nice course !

автор: 钱琨浔

Apr 28, 2017

very helpful

автор: Sourabh J

Nov 05, 2016

Good course!

автор: 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.

автор: 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.

автор: 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.

автор: Steven P

Nov 14, 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.

автор: 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.

автор: Shengliang D

Jan 18, 2020

The contents are well organized and arranged corresponding to the textbook Theoretical Neuroscience. There are supplementary materials for the lecture of each week. The assignments are very helpful for understanding the lectures, with code and data for Matlab, Python 2 and Python 3, which is very friendly for people who are only familiar with some of them. It would be better if the assignments could cover more about the lecture.

автор: Wojtek P

Jul 08, 2017

Extremely interesting subject, many ideas and methods presented. Basic disadvantage is a method of source which is closer to seminar rather than leacture. But, lost of details is acceptable due to a huge amount of material. Advanced mathematics from various areas is necessary to fully understand all the ideas. Anyway, I recommend the course.