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

4.0
stars
808 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

AK

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.

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.

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176 - 200 of 217 Reviews for Introduction to Trading, Machine Learning & GCP

By Animesh

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Jan 18, 2020

Not much learn from them, but whatever is there it's good.

By JL B

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Jan 11, 2020

Material sometimes seems like a patchwork in random order.

By Juan J M C

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Dec 27, 2020

some videos are from other courses.. not exist practice

By Joe M

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Apr 1, 2020

Good intro to concepts. Labs could use more thought.

By Alain T

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Apr 4, 2020

Good Introduction to Time Series, ML and GCP!

By Marck L

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Feb 25, 2024

Poor course overall, would not recommend. Looks like it has been put together by taking different parts from other courses, so it has a very incoherent feel to it and lacks any real structure. Moreover, the content is generally too superficial and the practical examples are extremely clunky to try and go through. The financial knowledge is good but the accompanying slides the lecturer goes through are poor. They only mention the topic he is talking about rather than contain any detail to help teach the concept. Hence, the lecturer is merely reading from a script here so it is more difficult to follow.

By Sam F

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Jan 3, 2020

Had I not read another book on ML, I probably wouldn't understand a lot of material covered here. The course might be a good recap if you already know the material. However for someone who is new to ML, the videos just dumps a lot of definition on you without real explanation in layman term. I ended up having to go to other YouTube videos for explanation.

By Bartłomiej N

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Nov 14, 2021

Course is OK but one of the labs is broken and the provided commands don't work and other one has a jupyter notebook with use of outdated python library for ARIMA and it doesn't work with new version

By Oleksandr S

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Feb 2, 2020

The course gives you a very limited introduction to ML for trading. More examples of time series models, basic trading strategies, use of ML methods etc are needed.

By Adrien S

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Oct 28, 2020

The course was ok but a bit disjointed, especially week 4 which felt like it was "cut-and-pasted" into the course from other courses and didn't have much cohesion.

By Alexander K

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Jan 31, 2022

Course may have some interesting instruction but about half of it is an elaborate advertisement for unnecessary google products. Not worth it.

By Dan B

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Nov 26, 2022

This course doesn't go into detail about finance or reinforcement learning. The labs are largely broken.

By Jonathan S

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Sep 13, 2020

Actual programming was nonexistent, the assignments just had you run already-written jupyter notebooks

By Ayush k

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Nov 15, 2023

The lecture content is great but the labs are not working at all... moving on to a different course

By Michael K

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Jan 23, 2020

Lacks depth of most topics , too brief of an introduction

By Yaron G

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Jun 22, 2020

Not sure it is good material for real tradings bots

By Harshit M

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Jun 12, 2020

No labs or quizzes for auditing students

By Guillermo B

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Aug 7, 2020

Very few real practical exercises.

By Atif H

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Jul 16, 2022

too basic.

By Egor D

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Jan 25, 2023

The overview of finance is fine, but the ML is instructed in a very basic and bad manner. The labs are just a torture. All you need is either copy-paste commands from the instruction or run all the cells in the notebook. No thinking, no sir. And in order to do these "assignments" they don't use coursera's local notebooks and grader, no. They use GCP, in incognito mode, and there are problems: 1. GCP's interface changed, so some of the labs' guidelines are not much relevant and you need to find stuff yourself.

2. For jupyter notebook, the education notebook itself is not the most time-consuming part. You will login to GCP, create notebook, wait ten minutes for it to be created (but GCP won't show it, you need to close the tab and relogin to GCP again to see "open jupyterlab"). And then, after 10 minutes you run and read all the cells for a minute. Yep, time management

3. Btw, GCP is in incognito mode. What if it forgets you right in the middle of "education" process? Say you do "git clone" or run the notebook and bum, nothing works, GCP asks you to re-login. Yea, boy, start all over: login, create notebook, wait for it to say "open jupyterlab", etc... Summary, the finance part seem good and clear. ML part is weak. Labs are just torture to waste of time and nerves. Questions they ask also are unclear and structured in a pattern matching manner of "words from lecture - question". One of the worst courses I've ever head. I hope they won't train Neural nets in SQL in the next ones (god bless)

By Steven K

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Dec 22, 2019

The required labs for passing are not uploaded and there is no support in the discussion forums. This means you can not effectively undertake this course without recreating the required cloud systems yourself.

Also, the content is massively outdated and uses an old version of tensor flow which is now deprecated. The course feels like its around 3 years old but only just been uploaded to coursera now.

Very poor experience in my humble opinion and I want my 2 hours of troubleshooting this back.

By Conor W

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Jan 21, 2020

A waste of time and money really. Appears to cobbled together from other courses. It doesnt flow, instead jumps around on random topics and none of them link up. It can jump from very basic concepts to suddenly covering complex topics in the in a 2 minute video. The "graded" exercises are pointless. Just following a series of (convoluted) steps and nothing is learned and nothing is actually graded. Dont waste you time with this.

By Allen S

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Aug 23, 2020

There could be some useful information in there but even with subtitles, the horrible audio quality makes it much too painful to wade through. I gave up and cancelled the course. I'm very disappointed as my cloud experience is entirely AWS and I was looking forward to learning about the Google Cloud alternative. How could a company as strong as Google produce such a staggeringly poor introduction to their platform?

By Luiz P F

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Oct 22, 2020

There seems to much detail lacking in both ML and Trading aspects of the course. Moreover, the practice labs are not interactive and don't build up to add much to the content. There's not much exploration during labs either. Overall, a very poor introduction.

By Jodon K

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May 31, 2021

The lectures are good. The coursework is atrociously bad. It appears to be pulled from a bunch of unrelated courses on both ML and BigQuery. The lectures are worth a listen, but I didn't come away having learned anything about programming ML for Trading.