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Introduction to Trading, Machine Learning & GCP に戻る

Google Cloud による Introduction to Trading, Machine Learning & GCP の受講者のレビューおよびフィードバック



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)....



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.


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.


Introduction to Trading, Machine Learning & GCP: 101 - 125 / 181 レビュー

by Samuel T


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

by Martin L


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

by Benjamin P


Not as much coding as I would have wanted, or atleast exposure to code. Very solid historical context though.

by Mike M


Pretty great course. Sometimes there was too much detail and other times not enough but overall I loved it.

by Brian B


Was pretty good. Would be nice to have some links to resources on BQML specific query language.

by Soren B


Good intro. Could use some additional work on the ARIMA model lab on tuning the parameters.

by Anirban S


Introduces concepts in a lucid way albeit depending on some prerequisite knowledge at times.

by Alejandro A S


the course is not very organized, the material presented are not clever in order

by Andrey S


Shortage of practice but good for learning something new about stock markets.

by Iskander R


Good as introductory course. Looking forward for more in depth topics. Thanks

by Alvar S I


Muy bueno por conjugar muy bien el mercado de capitales con la programación

by Sergio G


Easy to follow. It lacks of a more applied number of examples and cases.

by Ocin L


More explanation on the lab and the function being use would be great!

by Yip Y C


Course content should include more practical in each section



Nice course but showing only the peak of the GCP iceberg!!!

by Kong


Overall good experience. But first lab is confusing.

by domenico r


I was expecting more coding on python

by Robin L


please add more hands-on lab

by Wolfgang B


Yes. Introduction level.

by David C C R


Introductory course.

by Henry M


Good introduction

by Rayantha S


Very good course

by Sergio O



by Paolo D


I found this course to be very approximate as if it just wanted to give a high-level idea of the concepts it covered. But maybe, that is the actual goal of the course: give an idea of how ML concepts can be applied to the finance domain and then let the student deepen and practice with the techniques shown. The parts that I've found to give more interesting, even though they have not been covered in detail, are the quant strategies and the time series one. The ML part, coming from an ML background, is well explained but they have been formulated only to give a high-level idea without going into the mathematical details(which I think it's outside of the scope of this course). Regarding the lab part, I didn't enjoy the BiqQuery part while I've loved the lab with Jupiter notebooks (I'm a little biased here). I would have liked more math details, but again that is just a personal preference.

by Alexey L


First 3 weeks were quite good, although I found lack of lab practice. The time limitations on using GCP account were slightly pushing to complete it fast without having time for thorough thinking and experimenting. Although they could be restarted - the work had to be recreated again when this happened. Last week was very shallow and non-consequent and looked like it should be the first week as there were explanations of ML and GCP AI Notebooks. Which had been used during already during the first 3 weeks. Although I'm impressed with GCP platform and its AI capabilities, I felt like it had been highly advertised and selling though the course, where my personal preference would be learning more of algorithms and experimenting and using GCP just as one a tool.