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.
创建者 Joost v T•
Dec 2, 2020
Great course with great lectures given by great people. I liked the variety of topics in the course and all the fun little jokes and trivia offered in the lectures. The quizes were of fairly high level for me, so I really feel like I've learned something new. I would have liked to have exercises before trying the quiz though. And after the quiz it was hard to see what went wrong.
创建者 Wojtek P•
Jul 8, 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.
创建者 Víthor R F•
Mar 10, 2018
Many of the lectures do not make a plenty of sense relative to their quizzes. The lectures are rather theoretical and the quizzes are rather practical. Also, one of the professors have better didactics than the other. Either way, it was quite an adventure (my hat almost didn't survive).
创建者 Manuel P•
Dec 15, 2017
I enjoyed the course very much and hopefully learned quite a bit about how to model neurons and some interesting new ways to look at methods like perceptrons and PCA. The course videos are short by very dense. Make sure you make enough notes and prepare enough time for all of them.
创建者 george v•
Mar 18, 2017
Very good teaching skills by both professors and interesting guest lectures and tutorials. Assignements that demand your full attention. I would like some more depth as far as the developement of programming skills and the practice. Great intuition and explanation.
Mar 15, 2018
This course provides you with a brief introduction to computational neural science. You can benefit from it as long as you have basis in calculus and linear algebra. But for those who want to get the best from it, you need to build up your mathematics.
创建者 Krasin G•
Nov 16, 2016
This is a very interesting course that provides many interesting ideas. At the same time it is quite challenging. Solid background in probability theory, linear algebra and signal processing is needed. Considering it "Introductory" level is misleading.
创建者 Marek C•
Apr 9, 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.
创建者 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 :-)
创建者 Medha S•
Feb 25, 2021
It was a little difficult to get all the mathematical concepts in such a short time, but I really enjoyed the course and it gave me a good insight of what computational neuroscience encompasses.
Thank you for a wonderful course!
创建者 Adrian M•
Apr 3, 2021
Maybe adding more coding examples during course videos might be useful to get a better understanding of how to implement the concepts. Quiz code questions are good for that, but maybe more guided examples might be great.
创建者 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.
创建者 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.
创建者 Gustavo S•
Nov 15, 2016
Learnt concepts about Neural Networks, Supervised / Unsupervised / Reinforcement Learning. Covers topics about Information Theory, Statistic and Probability. Matlab / Python assignments.
创建者 Beatriz B•
Aug 3, 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.
创建者 Hui L•
Feb 25, 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.
创建者 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.
创建者 Anurag M•
Feb 3, 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.
创建者 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.
创建者 Driss A L•
Dec 2, 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.
创建者 Pho H•
Dec 27, 2018
Pretty good. A bit of mathematical ambiguity and lax notational conventions, but the course content was solid and presented clearly.
创建者 Ricardo C•
Oct 27, 2020
it delivers what it promisses: a first grasp of computational neurosciences, with a good overview of the fundamental concepts.
创建者 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.
创建者 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.
创建者 Moustafa M A M•
Nov 22, 2021
It was amazing journey diving deeply into the the brain and finding out how it works computationally