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

3.8
stars
326 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 75 Reviews for Fundamentals of Machine Learning in Finance

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 Gerardo O

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Mar 31, 2020

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.

By Jochen G

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Jan 22, 2022

Content of the course is superbe. However, the exams are a little outdated (tensor flow 1.x) and not well curated (buggy, lacking explanations, grader does not help) With help of the forums, one can pass.

By Jordan B

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May 11, 2023

Lectures are great -- good content and concise. The programming assignments on the other hand, are poorly designed and hard to grasp. Discussion boards seem to be abandoned by instructors and assistants.

By Deleted A

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Jun 5, 2020

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

By David C

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Dec 19, 2019

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

By Yi W

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May 10, 2022

The lecture is ok but lacks of details and the project is poorly designed without much guidance.

By Lingzi P

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Feb 24, 2019

the course content is okay. but the coding exam really needs improvement.

By Todd C

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Sep 4, 2023

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

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 Chaofan S

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Mar 19, 2020

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

By Arnav S

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Mar 17, 2020

Too bland. Reading off the slides. Couldn't understand anything.

By Ehsan F

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Feb 27, 2020

one of the worst courses I took in Coursera

By Wolfy G

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Nov 13, 2022

Lab issue not fixed