Chevron Left
Zurück zu Introduction to Trading, Machine Learning & GCP

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

4.0
Sterne
399 Bewertungen
113 Bewertungen

Über den Kurs

This course is for finance professionals, investment management professionals, and traders. Alternatively, this course can be for machine learning professionals who seek to apply their craft to trading strategies. At the end of the course you will be able to do the following: - Understand the fundamentals of trading, including the concept of trend, returns, stop-loss and volatility - Understand the differences between supervised/unsupervised and regression/classification machine learning models - Identify the profit source and structure of basic quantitative trading strategies - Gauge how well the model generalizes its learning - Explain the differences between regression and forecasting - Identify the steps needed to create development and implementation backtesters - Use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks To be successful in this course, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. 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-Bewertungen

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.

Filtern nach:

76 - 100 von 110 Bewertungen für Introduction to Trading, Machine Learning & GCP

von Henry M

Jan 19, 2020

Good introduction

von Rayantha S

May 07, 2020

Very good course

von Sergio O

Mar 28, 2020

Good!

von 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.

von 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.

von 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.

von 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?

von 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!

von 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.

von 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.

von mohammadreza s

Feb 16, 2020

the platform they chose for submitting homework was not very well. most of the time it took me 15min to get to the platform to code the homework. also, it doesn't dig deep into topics, which is fine because it is a comprehensive course.

von Nikolas M

Jan 14, 2020

Decent intro for ML but very limited in how it relates to trading. I would not say I feel comfortable creating an algo after this course. Also, felt very much like a Google ad quite often.

von Rustom F

Jan 30, 2020

The course seems to be more focused on advertising google cloud platform and there is hardly any focus on how to use ML or AI for trading.

von 欧阳坤

Jan 21, 2020

Too layman. NO real ML techniques for real trading, just some intro that you can easily find on stackoverflows or something.

von Pranesh R

May 05, 2020

I expected to understand how we'd interact with the exchanges and then run mdeols in realtime for trading outcomes

von Pranav K S

Jan 27, 2020

This is a good introduction course, fourth week completely different or not aligned with course title.

von Lazaris A

Mar 20, 2020

Nice theory very poor explaining in application not very useful to make you build a model

von Steve W

Dec 28, 2019

Some good parts, but several sections were cobbled together from other courses I've taken

von Hilmi E

Feb 01, 2020

The relationship between these three topics are somewhat loosely presented..

von Animesh

Jan 18, 2020

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

von Jean-Luc B

Jan 11, 2020

Material sometimes seems like a patchwork in random order.

von Joe M

Apr 02, 2020

Good intro to concepts. Labs could use more thought.

von Alain T

Apr 04, 2020

Good Introduction to Time Series, ML and GCP!

von Bryan D

Jan 13, 2020

Ok as an introduction (it is what the title says after all), but I ended up doing a lot of things in the lab without really knowing why I was doing them (e.g. loading different libraries, a lot of the syntax, etc.). Granted I can research that on my own, but more guidance would have been appreciated.

More broadly, this course feels a bit chaotic, jumping from one topic to the other, and then getting back at a previous one. This is ok to explore the fundamentals, which is clearly the intent here, but more structure would be welcome. Particularly, the introduction to Jupyter notebooks coming at the end of the course, after three labs, feels a bit frustrating. On a similar note, the course really feels like (and clearly is) something that was patched together from bits and pieces of other courses, with often times instructors referring to "previous" topics that were not actually covered (e.g. random forests). For a paid specialisation, this feels a bit sub-par. I have had free Coursera courses that felt more consistant.

von Sam F

Jan 03, 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.