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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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151 - 175 of 221 Reviews for Introduction to Trading, Machine Learning & GCP

By Mario E

Oct 17, 2020

I found the course introductory, not intermediate. There is no logical connection between the GCP part and its direct application to trading. Simple Notebooks would have been a better choice. The examples are pretty rudimentary but you can get some ideas here and there. The last week covering Deep Learning does not touch anything at all about Trading.

Not a memorable course, but at least it is lightweight. The Google part does not show any value in my opinion, it is like two independent courses in one.

By Chris C

Mar 13, 2021

Pulling the lessons and homeworks from other courses was probably necessary to keep the costs down and to make sure everyone is on the same page with the tools and procedures, so you're forgiven for doing that. I am looking forward to the next class so we can hopefully build on ARIMA and go beyond it to explore correlations between multiple time series and also how to do feature engineering that takes into account multiple time scales simultaneously (min, hour, day, week, year).

By Peixi Z

Jan 10, 2020

Like the finance aspect of things but the machine learning part seems to be pieced together from other lecture series and doesn't have great relevance to the trading topic. Also I am not here to learn the way Google do things albeit its power. You can run a separate ad channel if you want but why Coursera?

By tom t

Apr 20, 2023

The last assignment cannot be done in Hong Kong as the Jupyter cannot be opened using Singapore or Australia server.

Also, the AI platform has been upgraded by Google Cloud and it is now Vertex AI and not the AI platform before. The look and the button are placed in different areas.

By Abdulaziz A

Apr 17, 2020

Very well covered the theory of Training and its representation as a problem solving tool when it comes to predicting future prices, however the Machine Learning Part is not at all integrated to the Specialization (Trading) and also its content is not interconnected!

By Ahmed K

Mar 2, 2020

This course tries to be an introduction but it's not enough to give you an overview of ML and not well prepared also.

Labs are not encouraging to solve problems, it gives very trivial problem without focusing on enhancing your abilities on the learned subject.

By Manuel B

Apr 15, 2020

Useful as an introduction but feels like a patchwork of components that have not been developed in a consistent manner. For example the week 4 material is by and large a replication of a subset of what is found in the "How Google does AI/ML.

By Mohammadreza S

Feb 16, 2020

the platform they chose for submitting homework was not very well. most of the time it took me 15min to get to the platform to code the homework. also, it doesn't dig deep into topics, which is fine because it is a comprehensive course.

By Tiago C

Aug 16, 2020

The course has a few good points, but the lectures are often superficial. Also it seems like they are taking lectures from different courses and assembling them into one class, in a way that the lectures often seem disconnected.

By Nikolas M

Jan 13, 2020

Decent intro for ML but very limited in how it relates to trading. I would not say I feel comfortable creating an algo after this course. Also, felt very much like a Google ad quite often.

By rohit s

Jul 27, 2020

A decent introduction but with minimal hands on learning. Most of the initiative is on the student to learn about and apply the topics described here. Also tends to promote GCP a lot.

By Shekhar K

Jun 2, 2020

The course seems incomplete or not organized well. The concepts come and go out of nowhere. I knew lot of concepts beforehand and could figure out, but it was very fragmented.

By Kelvin C

Sep 1, 2020

The course is loosely organized. Some of the concepts in lab have not been gone through in the lecture. Anyway, the lectures presented by Jack is good.

By Andreas W

Sep 26, 2020

Theory of the financial part was interesting. "Coding" part was more or less running some fully implemented scripts from a github repository.

By Rustom F

Jan 30, 2020

The course seems to be more focused on advertising google cloud platform and there is hardly any focus on how to use ML or AI for trading.

By Michail A

May 26, 2022

Good introduction but would be better served with labs that force you to code more rather than do execute pre-existing commands

By 欧阳坤

Jan 21, 2020

Too layman. NO real ML techniques for real trading, just some intro that you can easily find on stackoverflows or something.

By Rafiul H N

Jun 2, 2020

The course was great from Google's point but from the "New York Institute of Finance", it was confusing and not helpful.

By Pranesh

May 5, 2020

I expected to understand how we'd interact with the exchanges and then run mdeols in realtime for trading outcomes

By Pranav K S

Jan 26, 2020

This is a good introduction course, fourth week completely different or not aligned with course title.

By Константин К

Aug 31, 2020

So many words in that course and so little knowledge. For me, it was wasting time on 80%.

By Angelos L

Mar 20, 2020

Nice theory very poor explaining in application not very useful to make you build a model

By Steve W

Dec 28, 2019

Some good parts, but several sections were cobbled together from other courses I've taken

By Hilmi E

Feb 1, 2020

The relationship between these three topics are somewhat loosely presented..

By Andy M

Aug 4, 2021

I would like to see more specific coding examples for trading strategies.