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.
This course is an excellent introduction to the field of computational neuroscience, with engaging lectures and interesting assignments that make learning the material easy.
par Marek C•
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•
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•
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 (•
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•
Learnt concepts about Neural Networks, Supervised / Unsupervised / Reinforcement Learning. Covers topics about Information Theory, Statistic and Probability. Matlab / Python assignments.
par Beatriz B•
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•
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•
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•
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.
par Akshay K J•
Overall - A good introductory course. But the last week, reinforcement learning and neural networks, could have involved programming questions.
par Driss A L•
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•
Pretty good. A bit of mathematical ambiguity and lax notational conventions, but the course content was solid and presented clearly.
par Ricardo C•
it delivers what it promisses: a first grasp of computational neurosciences, with a good overview of the fundamental concepts.
par Serena R•
I found this course helpful and inspiring for my research activity. I suggest it to anyone who has basic mathematical skills.
par Erik B•
Overall I enjoyed this class, but towards the end it gets more into machine learning and away from the neuroscience.
par Vanya E•
Great overview of a really cool field, gives nice intuitions for ideas in computational neuroscience.
Very interesting course, gained many skills of modelling that i am going to utilise in my research
par Jeff C•
In general very good, but some concepts are rushed over due to the short length of the course.
par Gaugain G•
Très bon cours je recommande pour tous les gens intéressé par les neurosciences théoriques
A better tittle for this course is 'From neuroscience to artificial intelligence'.
par Cezary W•
Quite interesting. I would see more explanation of some phenomena, though.
par Renaldas Z•
Great course, if a little bit outdated today.
par Huzi C•
Great course and really helpful for me.
par Abhilash C•
I like professor Rao's commentary.
par 배용희(대학원/일반대학원 물•
Best for the beginner.