學生對 New York University 提供的 Fundamentals of Machine Learning in Finance 的評價和反饋

The course is really challenging and requires a lot of self-motivated studying. I would say again it is the best course in quantitative finance that I have learned.

Furthered my understanding of how probabilistic models are connected to Machine Learning models. Very happy with the content in this course.

Great course which covers both theories as well as practical skills in the real implementations in the financial world.

This is a great course, I strongly recommend. However, the assignments take a while to finish.

Great class, but don't believe the programming assignment time estimates... takes way longer!

Excellent course to get ML algorithms for profit maximization approach

It's excellent and incomparable course!

Great explanations and great material

A great course with deep insight.

Very interesting arguments!

Very informative

thanks coursera

Thanks

The course offers a good review of techniques. The coding assignments can be improved, in my opinion. On the one hand, they are quite simplistic and do not require understanding of the course material, the algorithms or the theory to be completed - one just needs to mechanically follow the code and write appropriate lines. On the other hand, the grading algorithms are sometime stuck on technicalities that are not relevant either understanding or programming but may require significant time to figure out the correct solution.

For me, I find the math kind of useless. It's too hard for notice to understand, and too deep for those who don't want to know. This course should focus on its applications on finance. But at least you have few notebooks that you can keep for future reference.

Good material..The course would improve a lot if there were clear explanations for the goals of the assignments and the plan for the assignment.. The codes for the assignment should be fully debugged..

So far so good. The lecturer refers to projects of which some weren't covered in this course. So a little confusing. Takes lots of googling to finish this course.

Good course with relevant topics, but assignments are not clear sometimes, lack of support with them.

Add some hints in the notebooks, it was very hard to understand some parts

The course lecturing is good and having finance relevant examples is excellent but the programming exercises are very frustrating. The instructions are confusing and the final exercise requires a very long calculation that can time out. The forums are helpful though and it's all doable, a couple of tweaks and upgrading to Tensorflow2 would make this a 5* course

content of the lessons is quite good, I would give it 5 stars if the assignments weren't so buggy, contains mistakes, unclear instructions, no help from staff/moderator/instructor, technical issues that are not resolved, etc. a lot of frustration, it just feels like the course was rushed to production and they let the students debug it

Lectures assume that students know about Finance. For a person like me, all the finance terms are like jargon. Even though I have good knowledge of Machine Learning, the videos were difficult to follow. Not a very good amalgamation of Finance and Machine Learning.

Practical exercises are somehow disconnected from theory. Sometimes are not correctly guided and it is not clear the results they want to evaluate. Exercises can be done by navigating internet, the forums, but not reading the texts nor listening to the videos.

The programming assestment was uncorrelated to the content of the module, the main ideas are so great but thereis a problem connecting homework and content

Good lectures, but the problem sets are difficult, contain errors, little guidance, and no mentor or staff available to help with problems.