Chevron Left
Volver a Using Machine Learning in Trading and Finance

Opiniones y comentarios de aprendices correspondientes a Using Machine Learning in Trading and Finance por parte de Instituto de Finanzas de Nueva York

256 calificaciones
65 reseña

Acerca del Curso

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)....

Principales reseñas

30 de abr. de 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!

28 de feb. de 2020

The course is inspiring. It gave me another perspective of learning trading not just for Machine Learning also for day to day trading algorithm.

Filtrar por:

26 - 50 de 66 revisiones para Using Machine Learning in Trading and Finance

por Kris B

17 de mar. de 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).

por Jakub K

28 de ago. de 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.

por David N

31 de mar. de 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.

por Eugene L

19 de feb. de 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.

por Alexey L

9 de feb. de 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.

por Ikram U

23 de jun. de 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.

por Sajal S

7 de abr. de 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


8 de abr. de 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.

por Manuel Q

23 de may. de 2020

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

por Hilmi E

25 de feb. de 2020

Good material; packaging and presentation could be improved

por Sergio O

19 de abr. de 2020

God informative course! Some packages are not updated

por Henry M

30 de mar. de 2020

Feels very rushed.

por Piero R

13 de may. de 2020

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

por Naren T

26 de mar. de 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

por Antony J

23 de nov. de 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.

por Fernando G

26 de mar. de 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.

por Rene J R A

3 de feb. de 2021

This is one of the best courses in Machine learning for trading ever. It takes you deep into Tensorflow applying it to different trading strategies. 100% recommended if you're into machine learning for trading!

por Edgar C

7 de abr. de 2021

Excelente curso. Se entiende el uso del Machine Learning en Trading y Finanza..!

por Guilherme S S C

10 de abr. de 2020

Very Good! Basic strategies explored in depth and applied in coding labs.

por Sridhar S

24 de feb. de 2021

In GCP getting error while importing the data from Yahoo finance.

por Nicolas M

18 de mar. de 2020

Very good course. Applications are very useful and understandable

por Karthikeyan J

27 de feb. de 2021

good explanation of concepts and application of concepts


21 de mar. de 2021

Thank you for this amazing content =)


29 de abr. de 2021


por Emma A

4 de feb. de 2021

Thanks! - Emma