7. Apr. 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
10. Juni 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.
von Cezary W•
27. Sep. 2017
Quite interesting. I would see more explanation of some phenomena, though.
von Xiuyun W•
19. März 2020
I appreciate the effort of the lecturers to introduce so many interesting topics in such a short course, and the supplementary lectures by the TA are very helpful in understanding the concepts. However, as some other reviews have pointed out, the contents are too condensed and it jumped quickly from too simple to hard to understand. I guess it would be better if less topics are introduced but in more depth, or focused more on intuition under each topic rather than going into the maths without fully explaining them... I eventually reached a state of not really understanding the lecture videos but barely grasped some vague concepts. Then I can pass the quizes with full scores, without knowing what exactly I have learned or how I may apply them in real research...
von Bartłomiej L•
23. Mai 2017
I love the information that has been given there. The problem I have with the course (and it's a big one) is that you start each lecture with great detail and then go to what exactly you want to achieve. Because of this it was easiest for me to understand when I watched all the videos each week and then went backward to get it.
I highly recommend "start with why" videos and book by Simon Sinek, it might give you some info on how to make the lectures more comprehensive.
Having said this - the merit is great and I love having the knowledge. It is just that it isn't well laid out.
von Franz L•
17. Jan. 2021
I think the course has many improvement opportunities:
-Some lectures just jump from too simple to too complicated skipping important concepts. They could take more time to explain topics some of us are not experts at (as circuits analysis).
-There are no mentors who answer questions in the forums, and there are some very common doubts. Apparently, there are even some mistakes in the tests, where non of the answers is correct.
-There are no explanations about the correct answers in the tests. There are many questions I still don’t understand why the correct answer is X or Y.
-Some questions in the tests have much higher level than the one of the lectures.
-For my taste, Prof. Fairhall goes too fast in lectures. She could separate them into shorter videos, where she widely explains more focused topics.
On the other hand, it is a very interesting course. I really enjoyed explanations by Rich Pang in the supplementary video tutorials, as well as the lectures of Prof. Rao.
von Mathew T K•
4. Juni 2020
The course started out quite well, but increasingly became very difficult to follow. Instruction during the second week through the fifth week was particularly difficult for me to understand. Only the additional lectures by Rich made sense, but didn't go deep enough to help me understand the course material.
von Andrada T•
2. Dez. 2019
von Marta M•
11. März 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.
von Max G•
16. März 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.
von Victor G•
5. Juli 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!
von Vikrant J•
16. März 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
von Shwetank P•
27. Apr. 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.
von Sergey A R•
4. Nov. 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! :)
von Iván E A•
22. Dez. 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.
von Prachi S•
13. Dez. 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.
von André M•
20. Nov. 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.
von Daniel B•
2. Dez. 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.
von Diego B•
7. Apr. 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.
von Julieth L C•
11. Sep. 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.
von Amir Y•
1. Aug. 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.
von AmirHossein E•
26. März 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.
von Deepak R V•
1. Dez. 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
von Rohit P•
4. Juni 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!
von Matthew W•
23. Juni 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!
von Lucas S S•
28. Juli 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)
von Denis L•
8. Juni 2021
an excellent course for machine learning specialists who are interested in the nature-based principles of computing systems. unfortunately, the course does not have may examples of solving practical problems related to writing code, designing network architectures, usiing spikes etc.