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

4.0
stars
819 ratings

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

AK

May 28, 2020

Very interesting course, I totally agree that there are very few courses that cover time-series analysis. I haven't tried BigQuery before. Looking forward to next courses in this specialization.

MS

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.

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26 - 50 of 221 Reviews for Introduction to Trading, Machine Learning & GCP

By ASHISH D

Dec 29, 2019

Awesome learning.

By Emre K

Dec 23, 2019

Very helpful.

By Atichat P

Dec 28, 2019

Good

By Meisam M

Dec 24, 2019

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

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 Oleksandr

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 B

Mar 9, 2020

Great course

By Raguram S

Feb 8, 2020

Great Course

By Gabi M

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 Холодков Ю

Dec 8, 2021

Не системные знания, просто какие-то обрывки

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