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

820 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


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.


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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101 - 125 of 221 Reviews for Introduction to Trading, Machine Learning & GCP

By Leonardo A

Dec 22, 2020

Really good course

By Tuan V

Jan 26, 2024

should be updated

By Achraf J

Jan 11, 2023

Great course!

By j.guadalupe o

Mar 2, 2020

good course

By Gregory G J

Jan 23, 2021

Thumbs Up!


Sep 19, 2022


By LiengPhu T

Jun 26, 2021


By Prathamesh K

Sep 25, 2022


By Marcin G

Feb 6, 2021


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 Ryan S

Aug 26, 2023

Timely and relevant information pertaining to Machine Learning and Trading is covered within this course's content. Combinations of the New York Institute of Finance's expertise and Googles sheer power make for a good learning experience that maintains the students' attention. Having an understanding of online notebooks, specifically Google Cloud notebooks, is highly recommended.

By Jair R

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 Angelo M

Jul 25, 2021

The first module has a lot of specific knowledge of the financial market that it would not be easy to gather by conducting an extensive internet search. I realized that the professors have an excellent experience in the financial market, which greatly improves the final quality of the course.

By Carlos V M

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 Bernardo H

Jul 16, 2023

I liked the course teaching, materials, flow and hands-on exercises. I am not giving it five star, as the coding exercises could have been more learning focused rather that solutions showcasing focused

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 Shailendra k v

Jan 18, 2022

Good material... Assignment are very helpful. Flow is bit choppy specially for ML parts. It switches from simple to advance topic rather randomly.

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 Martin L

Jul 14, 2021

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

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.


Aug 9, 2022

Pretty basic concepts, although being titled as "Introduction" it does what it is supposed to do. Good job.