- 7 reviews
- 7 completed
'Introduction to neuoeconomics' is about the neural mechanisms for behavior and decision making. The video lectures are really top-class, it is one of the best edited course that I've seen on coursera. The sound and video quality are really good, and clearly a huge amount of effort was put to planning, rehearsing and editing the lectures. The pacing of the course seems to be a bit slow, at least at the beginning. Also, the quizzes are quite easy so far - I guess that's because this is basically an intro course. It would be great to have more engaging assignments, e.g. planning simple neuroeconomics experiments, interpreting results, etc. The syllabus seems very promising. The lectures so far were good, and the core concepts well explained. My only problem with the course is the recommendation of supplementary material. Instead of telling "You should read a lot more about this topic if your are interested" in the middle of the lecture, there could be a section at the end of each topic to recommend the best sources. (I'm aware that there are recommended readings in the 'Course plan', but implementing recommendations in the videos could be a good idea).
I only took this course because it is part of data science specialization. But the topic proved to be really interesting, and I got hooked quite fast. I liked the assignments too. The only small annoyance was the recorded classroom lectures, which were sometimes slightly redundant and not of good (sound) quality. It is a relatively easy course.
It is an important lecture, but maybe it needs some improvement. Although I understand that the lecturer did not want to explain every data type, some concepts were not very well explained (e.g. I'm still quite unsure about how to handle JSON format).
Although an important course, it had some really weak points. For example IMHO it was completely unnecessary to teach Git Bash (which is for weirdos), if the GIT Hub works just fine for the average users. The lecturer sounded quite bored too.
The course was very similar to reading an extremely boring mathematical statistics handbook. The presence of the lecturer did not bear any additional value, as he was not making too much effort to use educational methods to convey the material. He used very few (and generally uninteresting) examples, and did not structure the lectures to capture attention. The explanations were purely mathematical, thus difficult to comprehend, at least for me with a non- math background. The lecturer clearly not designed this course to an "educated general audience" (i.e. I presume most mooc takers). In order to understand the core concepts, I finally ended up on other moocs and sites on the same topic. BTW some of these external sources used no complex formulas, but were able to explain key concepts in very short time, using examples and graphical presentations. I hope this course will improve in the future, there is certainly a lot of room for that. From the third week, the course started to become better, even useful in the fourt week! So hang on!
I always wanted to learn R, and this course was a really good jump-in point. The course's scope is really good, the lectures were clear, and the lecturer convincing and professional.
This was a really informative course from a really good teacher! I learned a lot!