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Learner Reviews & Feedback for Introduction to Trading, Machine Learning & GCP by Google Cloud

561 ratings
153 reviews

About the Course

In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. 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

Jan 29, 2020

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.

Nov 20, 2020

I thought this was excellent. Some familiarity with standard SQL is needed to get the most benefit from the materials, and the course is clearly aimed at GCP users.

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26 - 50 of 151 Reviews for Introduction to Trading, Machine Learning & GCP

By jamesguo

Feb 15, 2020

a bit too easy, looking forward to next courses

By Albert W D P

Jan 13, 2020

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.

By Silviu M

Dec 27, 2019

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!

By Mohammad S A

Jun 12, 2020

I generally have high respect for whoever teaches me something useful, but I have to tell my try opinion here. Maybe passing other online courses has risen my expectations, and that it the reason I give two stars to this course. So here are my critiques to this course: 1- The contents are at different difficulty levels in this course, for example, the explanation on ML are very elementary, while the programming assignments are for advanced programmers proficient in SQL, Python, BiqQuery, ...

2- The material is not coherent. It doesn't start with general and straightforward explanations and then gradually elaborate on the details—3- The method of lecturing. I had to close my eyes while listening to some of the lecturers because the way of lecturing is very unnatural, and it is a distraction. Sometimes watching the presenter helps in learning because you can connect to their mind, but sometimes their hand movements, gestures, the way they look at the camera, and all these things are simply distractions.

But I must also mention some advantages of this course. 1- You will learn about some keywords on the topic of Trading using ML. You can generally understand what's going on in this area and what are the tools being used. 2- You'll find some links to useful resources so you can self-study and go through the direction you desire.

Anyway, I am sure this course will gradually improve after feedback from learners.

By Oleksandr I

Jan 17, 2020

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.

By Cesar V

Jun 16, 2020

Sorry, this is a mess.

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

By Martin S

Jan 30, 2020

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.

By Ricardo B G

Jan 21, 2020

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

By Kar T Q

Feb 1, 2020

Excellent introduction

By Leonardo G B

Mar 9, 2020

Great course

By Raguram S

Feb 8, 2020

Great Course

By Gabija

Feb 2, 2020

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.

By Marcos F

Jan 21, 2020

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

By Abby M

Mar 8, 2020

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

By Manfred R

Mar 8, 2020

The instructors presented their topics very clear and understandable.

By Chaikit R

Feb 21, 2020

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

By Rodrigo L D

Feb 18, 2020

Good introduction to ML and GCP, shallow content on Trading

By Filip Š

Jan 2, 2020

Rather easy

By Bryan D

Jan 13, 2020

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.

By Yue C

Jan 11, 2020

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.

By Esteban Z

Jan 17, 2020

One could basically get a very high grade just copying, pasting and clicking SHIFT + ENTER

By John Q

Mar 2, 2020

of all the courses I've taken at Coursera, and I admit many times I took on too many courses at once and only partially finished. .....this one was the worst. Poorly put together, almost a mish-mash. Lectures that had a true information content of maybe 20%, presenters who on video were simply reading a script, Quizzes that were trivial to pass, Exercises/Labs that were no better than copy-paste exercises (or typing exercises if you felt that represented value). It's like they had to put together *something* for a 4 week course, so each part of the team got one of those weeks, ... and no one ever got together to review the overall gestalt. And, some of the videos were clearly coddled together from other only semi-randomly related courses. I shudder to think what would happen to Coursera if more of their courses were like this. A major FAIL for online learning.

By Pedro S

Jun 7, 2020

Not very well structured, not coding explanation or training, you can fail the quiz as many times you like, re do them 100 times, and get a perfect score. Some concepts are well explained, but for example, when that guy explained about the neural networks, he started talking as if I was a expert on neural networks. I wont be posting this certificate on my Linkedin account, because after doing this course, I do not feel that I have learn enough to say that I understand ML.

By Deleted A

Jan 18, 2020

The course is mostly an advertisement for google cloud. What little there is about ML is a freshman 101 course — targeted at someone who has no idea, not practitioners as the syllabus suggests. But mostly, it’s about google cloud.


Jan 8, 2020

good introductory to ML and AI. however in the context of mostly trading, which is typically a regression problem. useful for some one who is new to ML and looking to learn or get exposed to possible use cases of ML and AI. Advanced users, probably know most of these techniques