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

4.0
stars
565 ratings
154 reviews

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

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.

AJ
Nov 20, 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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76 - 100 of 152 Reviews for Introduction to Trading, Machine Learning & GCP

By Leonardo A

Dec 22, 2020

Really good course

By J G

Mar 2, 2020

good course

By Andrei L

Apr 16, 2020

I can only agree with previouss comments:

1) Overall Ok as an introductory course

2) Week 4 should be week 1

3) Week 4 videos are somewhat disjoint and by the references they make are clearly just fragments of other courses.

4) Concepts used in labs should be explained a bit better beforehand

5) Each lab should have a at lease one concrete try-this followed by an explanation of why the result is different, better or worse

By Jair E R L

Jun 2, 2020

The course provides valuable content. It requires more than Python fundamentals in some topics, but it is ok because the student must investigate out of the course's material.

There is an emphasis on Google's tools, which are very interesting, but the course should be more agnostic on this matter in order that the student has wider spectrum of resources available.

By Jakub K

Aug 28, 2020

I learned a few cool things. The main problem with this specialization is that the Machine Learning Stuff and Finance stuff are really separated (Google, NY univ). What I was looking for is the place where two concepts meets. Also i felt like ML stuff went too deeply too fast. Still... Cool Introduction.

By Carlos V

Jan 19, 2020

Good course on the applications of ML to stock trading, examples are quite nice and the labs provide explanations on how to utilize the ML libraries available, recommended for anyone interested on more time-series type of analysis and ML

By Ramzy K

Jan 15, 2021

Very good intro to trading, despite the confusion from having multiple lectures collected from different courses, because they keep mentioning resources in the videos that doesn't relate to this course.

By Lucas R A

Jun 3, 2020

Good introduction to quant theory and ML, labs could be a lot better though, they lack proper explanations and don't cover some of the basics necessary to complete them.

By Debashish D G

May 5, 2020

The lectures appear to jump around a bit. Looks like it was stitched together from different places. So the course lacks a continuity I have seen in other courses.

By Piero R

May 11, 2020

It's a good course, but the volume is TOO LOW, and they don't go into detail in the programming phase for python. but it's good overall.

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 4, 2020

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

By Mike M

Apr 19, 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 14, 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 6, 2020

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

By Alvar S I

Sep 4, 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 Ocin L

Apr 10, 2020

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

By Yip Y C

May 9, 2020

Course content should include more practical in each section

By Kong

Jan 1, 2021

Overall good experience. But first lab is confusing.

By Domenico R

Apr 13, 2020

I was expecting more coding on python

By Robin L

Dec 21, 2020

please add more hands-on lab