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Learner Reviews & Feedback for Fundamentals of Machine Learning in Finance by New York University

3.7
stars
335 ratings

About the Course

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....

Top reviews

AT

Aug 9, 2019

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

AT

Sep 2, 2019

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

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51 - 75 of 79 Reviews for Fundamentals of Machine Learning in Finance

By Pavel K

•

Nov 28, 2018

Very informative

By mohamed h

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Dec 8, 2019

thanks coursera

By Dennis L

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Nov 16, 2022

Slow labs 4

By Zhao Y

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Sep 29, 2022

Thank you!

By Deleted A

•

Oct 31, 2021

Thank you!

By Cannie L

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Dec 30, 2020

Thanks

By Benny P

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Dec 11, 2019

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.

By Hilmi E

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Aug 5, 2018

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..

By Jacques J

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Dec 25, 2018

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.

By Aydar A

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Jun 27, 2019

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

By Sergey M

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Sep 11, 2021

I liked the course, but the bugs in the programming assignments are sometimes unbearable.

By Bozanian K

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Aug 19, 2018

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

By gareth o

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Sep 28, 2020

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

By Dossiman

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Oct 11, 2018

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

By Harsh T

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Mar 11, 2020

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.

By Todd C

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Sep 4, 2023

4.5 stars for lectures and <2 stars for homework design and environment

By andrew g

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May 16, 2024

The python notebooks are often difficult if not actually broken. This course is nearly impossible to complete without going into the discussions to see how people worked around the broken parts of the notebooks. Even with the extra help there, sometimes the notebooks just break anyway. The material in the lectures is decent, but the notebooks are nearly worthless.

By Shaun M L

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Feb 18, 2022

Course idea is very good and I enjoyed the content but the homework and projects are really terrible. The work is not hard I just struggle to understand what they are even asking me to do in some cirucmstances , the notebooks don't always work and I ran into problems trying to complete them that based on the discussion forum have been problems for over 2 years!

By Orestes S

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Jan 28, 2023

There are issues with the assignments! For example Weeks 4, one cells takes 90 minutes to run which is non-ideal. Course needs more attention from its creators as it can have potential!

By Mohammad A S ( S

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Mar 26, 2020

Not practical. Mainly just some complicated math formulas.

By Rudraroop R

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Jun 7, 2021

Utterly useless. Would give it zero stars if I could. The last assignment was just frustrating to complete, support is non existent, the lectures have little to do with the subsequent assignments, the assignments are outdated and teach you absolutely nothing about tensorflow as it is used today (read: who on earth doesn't use DENSE LAYERS in tf???). It's an absolute dump and I encourage you to stay away from this specialization altogether. Go do an Andrew Ng course instead if you want to learn something about Machine Learning. If you came into this with the object of expanding your ML knowledge into the financial realm and actually learning some finance along the way, then be assured that it won't help you accomplish anything. Hope I'm able to complete the specialization without smashing my computer in utter rage.

By Diego D

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Apr 28, 2021

Horrible course. It feels useless to follow it as the lectures are a bunch of topics that the instructor presents by giving superficial notions of them. The assignments barely relate to the lectures. Moreover the assignment notebooks are full of errors which makes hard to complete them. It seems that none care about this as the same issues have been highlighet by the students months after months and there is no support from the staff. I am disappointed in how Coursera has let the students down. Don't waste your money on this course.

By Amin D

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Dec 7, 2021

They did not spend 5 minutes on their assignment. You have to figure out the question and then find the answer by yourself. They do not teach what they ask for in assignment.

By Pablo M

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Aug 3, 2024

too many bugs and problems with weekly tasks. Spend more time trying to solve problems than learning about them. The videos and explanations are very good and complete.

By Chaofan S

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Mar 19, 2020

The assignment is not related to the contents and has bugs that no one responds.