Comentários e feedback de alunos de Guided Tour of Machine Learning in Finance da instituição New York University

Assignments are extremely difficult because the instructions are not clear. I understand that the act of working through the assignments is how you learn the material, however, this goes beyond that. It felt like a battle.

Great lectures. Homework is not trivial: it requires web searches and significantly more perseverance than, say, Andrew Ng's courses. Only 4 stars because I didn't see any recent signs of active support in the Forums.

The course seems a bit of date (tensorflow) and 'lazy' -- assignments are sloppy, not related to the content of lectures sometimes, sometimes just replay of things form reading material... Promised more than delivered.

Lectures are mostly short review of the topic. So you should know topics beforehand or supplement it with readings. Problems are great, you cannot solve it unless you understand the concept properly, so that good point.

Very interesting course. Covers the main algorithms of supervised machine learning and their applications to the world of finance. The one and only down is that programming session are a little hard to understand

Deep introduction into machine learning in finance. A bit outdated API-usage (Tensorflow 1), but nevertheless a great introduction for those who want to understand how the NN are processing the data.

Despite all the problems with the assignments and the grader this course provides really good overview ML tools and their application to finance. It's definitely worth the effort

The course content is a mix of theory and practical stuff. One star off is due to the poor quality of programming assignment, i.e., unclear instructions and explanations.

Good material but assignments explanation were too sparse and even expectation of material not covered in videos or readings (example is Tobit regression in week 4).

To much math in lectures, assignments are not coherent and complicated, im not sure that i need tensorflow from scratch to work with finance(Keras fits better)

Great general overview of machine learning. I think the course can be re-organized to incorporate some of the theory and some coding tips as well, however.

The Lectures and given readings are very useful and it is required to read them to complete the assignments which will otherwise be difficult

This will be a 5 star course when all of the technical issues are resolved. More timely feedback from the staff is desirable as well.

A more detailed introduction and guide to python for machine learning would have made this course one of the best out there

Very interesting content well delivered, the programming assignments could benefit from a little more guidance IMHO.

Great overview. Please provide more code examples as homework require a lot more than what the class covers!

Homework is not always consistent with what's covered in class. The recommended readings are very helpful.

One of assignments was hard. Explanation by lecturer was very easy to understand and appropriate long.

It would be great the background theory of related concept are explained in optional videos.

It's a good course. There are some missing explanations in the programming exercises.

Later assignmnets were difficult but lecture material is interesting and well taught.

Very good review and selected topics, although I would deep more on tensorflow use

The course content is okay, but the programming assignments are not well designed.

Great course, but the coding projects are sometime hard to understand

Learned ML concepts and algorithms to be used in financial work.