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Learner Reviews & Feedback for Using Machine Learning in Trading and Finance by New York Institute of Finance

3.9
stars
365 ratings

About the Course

This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....

Top reviews

BY

Dec 16, 2020

This the best online course I've ever joined, very practical, and could be able to implement in the real world with your own thoughts plus the hints from the course.

MM

Apr 30, 2020

This course was great!!! I think they skipped over a lot so it takes a lot of time to learn the details of the skills. But it definitely gives you the tools needed!

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26 - 50 of 109 Reviews for Using Machine Learning in Trading and Finance

By Esteban R F

Feb 28, 2020

Very interesting insights and new tools learned to improve trading algos and make smarter quantitative strategies

By Kris B

Mar 17, 2020

Some confusions in the quiz questions. Maybe it would be worth to review/ reformulate questions to make them clearer and more understandable. Some parts in the training are long “monologues”. It would be nice to add mode explicative slides concerning the discussed topic (less boring and better memorization for students).

By Jakub K

Aug 28, 2020

I learned a few cool things. The main problem with this specialization is that the Machine Learning Stuff and Finance stuff are really separated (Google, NY univ). What I was looking for is the place where two concepts meets. Also i felt like ML stuff went too deeply too fast. Still... Cool Introduction.

By David N

Mar 31, 2020

I really like the material but the Google platform had bugs. I don't think I got as much out of it as I would have liked. The concepts of the course are great and if they can fix the technical issues I encountered, it would be a really great learning vehicle. As it stands, it is a work in progress.

By Eugene L

Feb 19, 2020

IMO Aquan in the context to how it was deployed in this course is not a user friendly toolbox (aside from other minor technical difficulties). Good potential, it would have been better if it was accompanied with more lecture content.

By Alexey L

Feb 9, 2020

A lot of useful information but theory practice are quite disjoint. Code examples in the last video in section 2 along with non-clickable links are disappointing. In general the course is OK but could be done much better.

By Ikram U

Jun 23, 2020

Teaching was really good. Grading could have been better if assignments are properly graded before providing the certificate. One can simply go to assignment and without any updates, is marked as complete.

By Sajal S

Apr 7, 2020

they taught about the principle and all the stuffs but didn't make me comfortable to code.And this made me little bit dis-satisfactory with the course

By NILANJAN C

Apr 8, 2020

The course contents need to be updated and the students need to be working on editing the codes rather than just merely executing it.

By Manuel Q

May 23, 2020

The lectures are very interesting but look very uncorrelated with the activities. Looks like it is unfinished.

By Hilmi E

Feb 25, 2020

Good material; packaging and presentation could be improved

By Sergio O

Apr 19, 2020

God informative course! Some packages are not updated

By Henry M

Mar 30, 2020

Feels very rushed.

By Piero R

May 13, 2020

Labs are not updated and some codes doesnt work, making the whole practical part USELESS. otherwise the course gives you good theorical knowledge.

By Mazen S

Jun 22, 2023

Overall content is good, but it needs massive updating. Also, the labs are so out of date, they need to be reviewed

By Ilia K

Feb 24, 2023

The labs are junk. Half of them are broken, some of them are missing. Those that are working, are not good enough.

By Naren T

Mar 26, 2020

The audio for every lecture is horrible. Especially the coding solution lectures. The lab assignments are not engaging and poorly executed. A very disappointing course

By Souvik D

Jan 14, 2023

Almost all of the code that uses Auquan doesn't work. This course is deprecated.

By Antony J

Nov 23, 2020

Excellent foundational material, although there is a large variation (Keras Functional API, for example).

I liked the material on deep neural networks and Kalman filters, but not so much the if-then-else backtesting approach in one of th Auquan sessions; machine learning is intended to help humans move away from hard-coding these sorts of decision rules (I think).

Overall, very good, with something for everyone.

By Le R U

Jul 11, 2024

this course has taught me how important machine learning has been for the finance industry. Although not all the functions were working properly a couple months ago I can say that they are starting to become more popular and evidently clearer that this type of programming is crucial to the success of computerized trading. One algorithm I would also suggest is K-NN.

By Ryan S

Aug 27, 2023

Having looked quite extensively for a course on such a topic, I was thoroughly pleased upon coming to this one. Overall, the course flowed well and covered information very pertinent to the topic. High recommendations for this course and anyone seeking to learn about AI and Finance/Trading.

By Stanley F

Sep 5, 2021

This ML course gives you the necessary tools that will propel you to the new era of technology. Students get a hands on of the Google Cloud Platform as well as the nuts and bold and insight on trading technology nuances clearly delivered by the New York Institute of Finance.

By Dinh B P

Nov 30, 2022

very useful. Students could immediately practice on python with support code

of course it is complicate for someone have not learned about coding but we should spend more time to dig deeper to understand the code logic by another programing courses

By Fernando G

Mar 26, 2021

Great course! Learned a lot! However, I would recommend to include more useful solution videos for the labs. You practically see someone run the code without explaining much about the solution and/or underlying strategy.

By Bartłomiej N

Dec 3, 2021

Great content, nice speakers and interesting knowledge, the only issue I have are some of the labs are quite out of date with regards to libraries and APIs used, other than that it's great