Awesome learning.

Very helpful.

Good

some explanation in trading was hard, it was realy good to be able to test google cloud services, but needs more practical examples

a bit too easy, looking forward to next courses

I have taken multiple courses on Coursera. This course had particular strengths and weaknesses. For strengths, I certainly learned a fair amount from the course, particularly as it applied to ARIMA models for finance. For weaknesses, the course seemed to have been somewhat haphazardly thrown together. Week 4, the last week, was particularly poor. The lectures had little to do with one another and appeared pulled from multiple other sources. One was geared for people with advanced skills in mathematics and machine learning and was way out of my, and most people's, wheelhouse for learning.

Rather good content but I believe it is not always presented in the right order. In addition, some of the revision questions were extremely superficial. Last, I really don't like lecturers reading out the content from their laptops. I can do that by myself!

Almost no trading-related content (except the brief introduction in the 1st week).

ML content is poor comparing to other ML courses on Coursera. Instructors teach how to do simple ML tasks with some third-rate chargeable Google product (like SQL but with tweaks on it). In the course itself the product is free of charge, but why teach anyone to do this in paid software, when there is a lot of good open source solutions used in the industry?

Overall extremely poor trading and ML content is charged $50 per month, which is a too high price.

Sorry, this is a mess.

A frankestein of different coursers, you are much better with something like Quantopian.

Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.

Maybe Week 4 can be Week 1. It has the description of the tools used in the rest of the weeks.

Excellent introduction

Great course

Great Course

Giving 4 stars as there were some technical problems with AI Platform in week 3 and could not access the lab work, which is pretty disappointing.

A good intro to machine learning in finance. I does not goes very deep, but hat some useful exercises and practice with google cloud.

Great for beginners! A lot of examples and theories with practices. It let me learn more about the underlying principles.

The instructors presented their topics very clear and understandable.

Good point to start, but need to clarify more in some points.

Good introduction to ML and GCP, shallow content on Trading

Rather easy

Не системные знания, просто какие-то обрывки

Ok as an introduction (it is what the title says after all), but I ended up doing a lot of things in the lab without really knowing why I was doing them (e.g. loading different libraries, a lot of the syntax, etc.). Granted I can research that on my own, but more guidance would have been appreciated.

More broadly, this course feels a bit chaotic, jumping from one topic to the other, and then getting back at a previous one. This is ok to explore the fundamentals, which is clearly the intent here, but more structure would be welcome. Particularly, the introduction to Jupyter notebooks coming at the end of the course, after three labs, feels a bit frustrating. On a similar note, the course really feels like (and clearly is) something that was patched together from bits and pieces of other courses, with often times instructors referring to "previous" topics that were not actually covered (e.g. random forests). For a paid specialisation, this feels a bit sub-par. I have had free Coursera courses that felt more consistant.

Poor course overall, would not recommend. Looks like it has been put together by taking different parts from other courses, so it has a very incoherent feel to it and lacks any real structure. Moreover, the content is generally too superficial and the practical examples are extremely clunky to try and go through. The financial knowledge is good but the accompanying slides the lecturer goes through are poor. They only mention the topic he is talking about rather than contain any detail to help teach the concept. Hence, the lecturer is merely reading from a script here so it is more difficult to follow.

I am a AI research engineer and I can follow the technical content without problem. But I can imagine students who are new to these topics would get lost very quickly. In my opinion, this course talked very little about the fundamentals of the models, and I don't think anyone would be able to understand these models by taking this course.