Very useful course. Personally, I think that there should have been more focus on the implementation of tensorflow and neural network codes. Overall the course is well structured and very clear.
Introduction of ML for Financial application with combination of Scikit learn, Statsmodels and Tensorflow with neuralnets made this class very interesting. Learned and Enjoyed lot.
By EDGAR H M•
Muy buen curso aunque retador en sus trabajos de programación
Very good course! Thank you, Professor Igor Halperin
By Pavel K•
A very informative and well paced intro to ML / DL
By Luis A•
Excellent overview of machine learning in finance
By Sileye B•
I enjoyed thi introduction to ML for finance.
By mohamed h•
thanks coursera for this amazing course
By Yergali B•
Thank you, for this very useful course!
Great introduction to ML in Finance!
By Vilimir Y•
A great course by a great lecturer!
By Yuning C•
A great course with deep insight.
By Muntu M•
Excellent Course, Well presented
By Sreenath P K•
Very well taught course!
By Jenyi L Y•
very practical for me.
By Yangtao W•
very good course!!!
By Ezequiel A G•
By LiengPhu T•
Verry good !
By Vinay P K•
By Russell H•
Good overview of ML in Finance, clearly based on real-world experience. Would not recommend this as a first ML course; probably more useful after first taking another more general course, such as Guestrin's UW ML specialization. Some of the quizzes and exercises seem a bit rushed; e.g., out of order vs. the lectures and not clear about what is required. It was sometimes necessary to consult the discussion forums for clarification. The most useful part may be the categorization of ML algorithms along different axes, including applicability to different areas of finance. The readings and coding exercises seem to come mostly from Geron's O'Reilly book, so plan on buying that (it's a great book, so you should buy it whether you take this course or not).
By Benny P•
This course has been informative, and extremely FUN! This is not to say that it's perfect, in fact as others say the assignments are quite challenging because there's little introduction to the problem/solution being asked. But that's exactly where the fun is! You need to search for the information yourself to solve the problem, much like in the real world. In fact I took another course on TensorFlow in the middle of this course to finish the assignment. But I can imagine this would be frustrating for those with less background on ML or programming, or people who expect everything to be presented smoothly for them.
By Hashim M•
A much needed course by a very seasoned expert in the field, bringing the right blend of backgrounds in finance and tech. The course is well designed for finance professionals with some coding background and for technology professionals with some finance background - which is unique in that sense. Some bridging between lectures and assignments is needed but that kind of fine tuning is inevitable and as more students enroll, the discussion rooms and feedback will provide that sharpening at the edges organically. All in all, I enjoyed the course a lot and look forward to the next three in the specialization!
By gareth o•
Lectures are very good and the use of financial examples really brings the subject alive. However the final projects are not very closely linked to the material taught, it's possible to pass if you ignore the new material. It would also be nice to update the tensorflow code from 1.0 to 2.0 as it would make things much easier to debug.
By Pedro H•
Potentially great course with bridges technology (machine learning methods) and application (finance), but as for now it is really rough around the edges. Still needs to improve in terms of video lectures, resources and assignments; but once polished it could be a great course/specialization.
By Jose G H C•
Um curso um que demanda um pouco mais que o usual, partindo desde o princípio de um ritmo rápido, com tarefas contendo explicações de somente o estritamente necessário. Entretanto, com uma temática muito interessante, e utilizando de várias técnicas.