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

281 個評分
59 條評論


The course aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) understanding where the problem one faces lands on a general landscape of available ML methods, (2) understanding which particular ML approach(es) would be most appropriate for resolving the problem, and (3) ability to successfully implement a solution, and assess its performance. A learner with some or no previous knowledge of Machine Learning (ML) will get to know main algorithms of Supervised and Unsupervised Learning, and Reinforcement Learning, and will be able to use ML open source Python packages to design, test, and implement ML algorithms in Finance. Fundamentals of Machine Learning in Finance will provide more at-depth view of supervised, unsupervised, and reinforcement learning, and end up in a project on using unsupervised learning for implementing a simple portfolio trading strategy. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course....



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.


26 - Fundamentals of Machine Learning in Finance 的 50 個評論(共 57 個)

創建者 Wenxiao S


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.

創建者 Angelo J I T


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

創建者 Arditto T


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

創建者 Siyu D


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

創建者 Craig V


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

創建者 Alvaro M


Excellent course to get ML algorithms for profit maximization approach

創建者 刘晶


It's excellent and incomparable course!

創建者 Carlos S


Great explanations and great material

創建者 Yuning C


A great course with deep insight.

創建者 Stefano M T


Very interesting arguments!

創建者 Pavel K


Very informative

創建者 Mohamed H a e r


thanks coursera

創建者 Cannie L



創建者 Serguei Z


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.

創建者 Benny P


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.

創建者 Hilmi E


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..

創建者 Jacques J


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.

創建者 Aydar A


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

創建者 Bozanian K


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

創建者 gareth o


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

創建者 cyril c


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

創建者 Harsh T


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.

創建者 Gerardo O


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.

創建者 Juan C G A


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

創建者 David C


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