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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

3.9
490件の評価
140件のレビュー

コースについて

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)....

人気のレビュー

MS

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.

BA

Mar 16, 2020

Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.

フィルター:

Introduction to Trading, Machine Learning & GCP: 76 - 100 / 137 レビュー

by Samuel T

Jan 15, 2020

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 Benjamin P

Apr 04, 2020

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

by Mike M

Apr 20, 2020

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

by Soren B

Apr 21, 2020

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

by Anirban S

Jan 19, 2020

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

by Alejandro A S

Jul 15, 2020

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

by Andrey S

Jun 23, 2020

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

by Iskander R

Jun 06, 2020

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

by Alvar S I

Sep 05, 2020

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

by Sergio G

Apr 26, 2020

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

by OL

Apr 10, 2020

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

by Yip Y C

May 10, 2020

Course content should include more practical in each section

by Domenico R

Apr 13, 2020

I was expecting more coding on python

by Wolfgang B

May 05, 2020

Yes. Introduction level.

by David C C R

Apr 19, 2020

Introductory course.

by Henry M

Jan 19, 2020

Good introduction

by Rayantha S

May 07, 2020

Very good course

by Sergio O

Mar 28, 2020

Good!

by Alexey L

Jan 19, 2020

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.

by Biagio B

May 29, 2020

Most of the course is used to advertise GoogleCloud, in particular BigQuery, instead of teaching more general concepts. At least now I know what BigQuery is and, as a python programmer, I won't be using it since I don't want to learn a new language used and managed only by Google. The AI notebooks are awesome though! Exactly the opposite of BigQuery: uses a language and tools that everyone knows (python notebook) but on a virtual machine managed in the cloud. About the teachings, I learn a bit more about time series, but just the tip of the iceberg really, nothing applicable. Looking forward to the real deal, opefully in the next course.

by Loo T T

Mar 02, 2020

The course isn't really for complete beginner. It requires additional readings and googling on your own to understand the gaps. The labs are great to provide hands-on application (albeit requiring some knowledge of Pandas, scikit-learn and statsmodels) and but I feel that some of the content could have been discussed more in details in the video lectures or as supplementary readings. Nevertheless if you are willing to spend extra time researching to understand better, this course is still great for you.

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 Abdulaziz A

Apr 18, 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 02, 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.