Excellent training

Really good course

should be updated

Great course!

good course

Thumbs Up!

nice

good

/

Ql

I can only agree with previouss comments:

1) Overall Ok as an introductory course

2) Week 4 should be week 1

3) Week 4 videos are somewhat disjoint and by the references they make are clearly just fragments of other courses.

4) Concepts used in labs should be explained a bit better beforehand

5) Each lab should have a at lease one concrete try-this followed by an explanation of why the result is different, better or worse

Timely and relevant information pertaining to Machine Learning and Trading is covered within this course's content. Combinations of the New York Institute of Finance's expertise and Googles sheer power make for a good learning experience that maintains the students' attention. Having an understanding of online notebooks, specifically Google Cloud notebooks, is highly recommended.

The course provides valuable content. It requires more than Python fundamentals in some topics, but it is ok because the student must investigate out of the course's material.

There is an emphasis on Google's tools, which are very interesting, but the course should be more agnostic on this matter in order that the student has wider spectrum of resources available.

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.

The first module has a lot of specific knowledge of the financial market that it would not be easy to gather by conducting an extensive internet search. I realized that the professors have an excellent experience in the financial market, which greatly improves the final quality of the course.

Good course on the applications of ML to stock trading, examples are quite nice and the labs provide explanations on how to utilize the ML libraries available, recommended for anyone interested on more time-series type of analysis and ML

Very good intro to trading, despite the confusion from having multiple lectures collected from different courses, because they keep mentioning resources in the videos that doesn't relate to this course.

I liked the course teaching, materials, flow and hands-on exercises. I am not giving it five star, as the coding exercises could have been more learning focused rather that solutions showcasing focused

Not as prominent or important as the Finance specialization but important factor more so in the lifestyle factor of classification and could be useful to other fortune 500 companies.

Good introduction to quant theory and ML, labs could be a lot better though, they lack proper explanations and don't cover some of the basics necessary to complete them.

The lectures appear to jump around a bit. Looks like it was stitched together from different places. So the course lacks a continuity I have seen in other courses.

Good material... Assignment are very helpful. Flow is bit choppy specially for ML parts. It switches from simple to advance topic rather randomly.

It's a good course, but the volume is TOO LOW, and they don't go into detail in the programming phase for python. but it's good overall.

Some of the content in Week 4, might be better placed earlier in the course. Other than that it was a great learning experience.

Even are more basic knowledge of Trading and ML, still with specific data relative Trading and finance, Great!