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Kursteilnehmer-Bewertung und -Feedback für Introduction to Trading, Machine Learning & GCP von Google Cloud

658 Bewertungen
180 Bewertungen

Über den Kurs

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)....


29. Jan. 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.

20. Nov. 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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101 - 125 von 181 Bewertungen für Introduction to Trading, Machine Learning & GCP

von Samuel T

15. Jan. 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.

von Martin L

14. Juli 2021

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

von Benjamin P

4. Apr. 2020

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

von Mike M

19. Apr. 2020

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

von Brian B

8. Apr. 2021

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

von Soren B

21. Apr. 2020

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

von Anirban S

19. Jan. 2020

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

von Alejandro A S

14. Juli 2020

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

von Andrey S

23. Juni 2020

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

von Iskander R

6. Juni 2020

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

von Alvar S I

4. Sep. 2020

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

von Sergio G

26. Apr. 2020

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

von Ocin L

10. Apr. 2020

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

von Yip Y C

9. Mai 2020

Course content should include more practical in each section


2. Juli 2021

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

von Kong

1. Jan. 2021

Overall good experience. But first lab is confusing.

von domenico r

13. Apr. 2020

I was expecting more coding on python

von Robin L

21. Dez. 2020

please add more hands-on lab

von Wolfgang B

4. Mai 2020

Yes. Introduction level.

von David C C R

19. Apr. 2020

Introductory course.

von Henry M

19. Jan. 2020

Good introduction

von Rayantha S

7. Mai 2020

Very good course

von Sergio O

27. März 2020


von Paolo D

17. Juli 2021

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.

von Alexey L

19. Jan. 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.