Jack Farmer
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). We help millions of organizations empower their employees, serve their customers, and build …
Instructor Details
Courses : 3
Specification: Introduction to Trading, Machine Learning & GCP
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54 reviews for Introduction to Trading, Machine Learning & GCP
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 16 hours |
| Year | 2019 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Himalay O –
The course gave me a basic understanding of few types of models including linear regression, time series and neural networks. A few more offline exercises that we can perform on our own would be a good addition to assert the acquired knowledge even more.
ASHISH D –
Awesome learning.
HE J –
Too simple
Carson R –
Other courses recommended before doing this one! Basics of ML, Basics of the stock market, python and sql
Diderico v E –
Nice overview of the content. Well organized and effective.
Carlo R C –
This course is a pre sales demo of BigQuery. I thought GCP was partnering with the NY Institute of Finance to create the labs on VMs using GCP (which makes sense), but it turns out that the core information about the introduction to trading and ML is minimal, about 20 minutes of substance per week and the rest of the time is Google advertisement for BigQuery and GCP. The skewed theory from the videos ends up with a Google product guide of a specific, more skewed way of running a feature of a product. I thought this course would give me a proper introduction of ML for trading but instead is more focused on the google ecosystem. I would not recommend this course unless you want to learn more about Google Cloud Platform, BigQuery, TensorFlow or any other google product. The NY Institute of Finance fails to deliver the theory, it seems like google is telling the instructor what to talk about so google can show and tell about its products. You are better off buying a good book about ML for trading and read the google documentation about the products they have (if you want to use google), it’ll be cheaper and more time effective.
Gehad W –
Excellent course by Google and NY Institue of Finance. Course is well structured and provides high quality content with good labs. I much enjoyed Jack Farmer putting Quant strategies in a nice and clear structure while explaining complex topics in an intuitive and simple way. Time series and ARIMA modeling with the related lab is also a very good part. I hope the latest Tensorflow 2.x version will be used in next course.
Sam F –
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.
Filip ` –
Rather easy
Nelson F –
Fantastic course.
DAN T K –
Very nice course to understand liner regression, ARIMA and ML. Also, the practice on GCP with notebook is exciting to me
Juan R M O –
A lot of possibilities
Roberto R –
Great start material for ML and Cloud Computing
Saulo D S e R –
Very few information. Poor practical homeworks. Poor quiz. It seems the course really starts on the second course. The first course doesn’t worth the investment. It is more a show off of google products than a real course.
SENTHIL V K –
good introductory to ML and AI. however in the context of mostly trading, which is typically a regression problem. useful for some one who is new to ML and looking to learn or get exposed to possible use cases of ML and AI. Advanced users, probably know most of these techniques
Peixi Z –
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?
Gerardo G –
I am a physicist and I find it very basic, It did not provide me with any new knowledge whatsoever even with the little amount of knowledge I had of the subjects.
Jean–Luc B –
Material sometimes seems like a patchwork in random order.
Yue C –
I am a AI research engineer and I can follow the technical content without problem. But I can imagine students who are new to these topics would get lost very quickly. In my opinion, this course talked very little about the fundamentals of the models, and I don’t think anyone would be able to understand these models by taking this course.
Jean Luc B –
Material sometimes seems like a patchwork in random order.
Bryan D –
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.
Arunkumar M –
Great introduction for people who want to get started in ML, GCP and Fin Tech
Andrew –
Good course that gives a lot of breadth as an introduction to machine learning in finance. Well put together
Albert W D P –
I have taken multiple courses on Coursera. This course had particular strengths and weaknesses. For strengths, I certainly learned a fair amount from the course, particularly as it applied to ARIMA models for finance. For weaknesses, the course seemed to have been somewhat haphazardly thrown together. Week 4, the last week, was particularly poor. The lectures had little to do with one another and appeared pulled from multiple other sources. One was geared for people with advanced skills in mathematics and machine learning and was way out of my, and most people’s, wheelhouse for learning.
Seshadri S K –
Great course with Basics
Nikolas M –
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.
Samuel T –
Some of the content in Week 4, might be better placed earlier in the course. Other than that it was a great learning experience.
Gavin H –
Though the introduction said the course would focus on just trading and ML, it really is just a set of disjointed modules, often with nothing to do with trading, with little to keep it together. There is a lot of repetition between modules and they really look like they have just been pulled out of other courses. In the final week, the one video even mentions and exercise that does not exist.
Steve H –
Good intro to ML and using GCP.
Esteban Z –
One could basically get a very high grade just copying, pasting and clicking SHIFT + ENTER
Oleksandr I –
Almost no trading related content (except the brief introduction in the 1st week). ML content is poor comparing to other ML courses on Coursera. Instructors teach how to do simple ML tasks with some third rate chargeable Google product (like SQL but with tweaks on it). In the course itself the product is free of charge, but why teach anyone to do this in paid software, when there is a lot of good open source solutions used in the industry? Overall extremely poor trading and ML content is charged $50 per month, which is a too high price.
Animesh –
Not much learn from them, but whatever is there it’s good.
Joe –
The course is mostly an advertisement for google cloud. What little there is about ML is a freshman 101 course — targeted at someone who has no idea, not practitioners as the syllabus suggests. But mostly, it’s about google cloud.
Henry M –
Good introduction
Alexey L –
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.
Anirban S –
Introduces concepts in a lucid way albeit depending on some prerequisite knowledge at times.
Carlos V –
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
Marcos F –
A good intro to machine learning in finance. I does not goes very deep, but hat some useful exercises and practice with google cloud.
Conor W –
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.
Ricardo B –
Maybe Week 4 can be Week 1. It has the description of the tools used in the rest of the weeks.
Michael K –
Lacks depth of most topics , too brief of an introduction
Pranav K S –
This is a good introduction course, fourth week completely different or not aligned with course title.
Martin S –
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.
Rustom F –
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.
Hilmi E –
The relationship between these three topics are somewhat loosely presented..
Kar T Q –
Excellent introduction
Gabija –
Giving 4 stars as there were some technical problems with AI Platform in week 3 and could not access the lab work, which is pretty disappointing.
Oleksandr S –
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.
Edward L –
Constant headaches trying to get GCP to work. Even if you do get it to run without crashing (unlikely) you don’t really learn much in the labs because they are already 100% written for you its just run this code we provided.
Raguram S –
Great Course
jamesguo –
a bit too easy, looking forward to next courses
mohammadreza s –
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.
Ralph S –
Great introduction course that gives you an idea of various concepts of machine learning
Sergio O –
Good!