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

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).

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.

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.

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.

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.

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.

Trading tactics are good for new investors. Half the Labs are obsolete and do not run. My primary objective was the programing portion, so this was disappointing.

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

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

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

there are many codes don't work because it is not updated or maintenanced.

Good material; packaging and presentation could be improved

God informative course! Some packages are not updated

Feels very rushed.

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

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 Also, the labs are so out of date, they need to be reviewed

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

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

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

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.

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.

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.

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.

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