In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy.
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).
Status: Markov Model
Markov Model
Status: Financial Trading
Financial Trading
Intermediate·Course·12 hours
Featured reviews
5.0
·Reviewed Mar 5, 2020
It was easy to follow but not easy. I learned a lot and I now have the confidence to implement Reinforcement learning to my own FX trading strategies. Thank you so much.
4.0
·Reviewed Jul 1, 2022
I look forward to examples of integration of decision based on reinforcement learning and algo-trading logic
4.0
·Reviewed Jul 13, 2021
Provide the idea and method of RL for trading, but seems like less practice knowledge for the trading. hope can add more detail for for the trading build up. overall the course are good.
4.0
·Reviewed Apr 6, 2020
It has good practical stuff, BUT not any practical RL related to trading.
5.0
·Reviewed Feb 2, 2021
After the first two courses, this one grabs you into the reinforcement learning spectrum. This topic has been revealing to me and its applications to trading
4.0
·Reviewed Mar 14, 2020
Good course introducing concepts in RL. Wish course provided more examples of using RL in stock prediction.
5.0
·Reviewed Sep 10, 2024
It's Intensive and Inclusive, but please make sure all labs work smoothly.
4.0
·Reviewed Jul 18, 2020
perhaps an applied trading notebook would have been nice...I understand that liability issues might have arisen, but there might have been a reasonable avenue with repeat disclaimers, etc
5.0
·Reviewed May 19, 2021
Succinct and great explanation of deep reinforcement learning methods with amazing demo lab scripts
4.0
·Reviewed Jul 12, 2021
A touhg and very advanced course, with an amazing Google Cloud Platform !!!!
5.0
·Reviewed Mar 6, 2020
Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn
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Y
Yutong
1.0
·Reviewed Apr 27, 2020
I think this course is in the middle of a simple introduction and a practical course. You should not enroll if you expect to be able to be able to build a RL system. You should not enroll if you are expecting some simple intuitive introduction of RL. This is more difficult than an introduction but tells you nothing more than some introduction, so it is an introduction done in a difficult way. I think it is better to avoid it.
J
Jiaheng
1.0
·Reviewed May 3, 2020
Only learned small pieces of concepts about quant trading, reinforcement learning parts are not connected well at all, it's all about advertising Google Cloud services.
N
Nissims
1.0
·Reviewed Feb 20, 2020
Disapponting.
Last project week 3 does not have any connection to the topic.
Most of week 3 lessons are hand waving general recommendations, not real teaching or discussions
I feel deceived.
B
Brian
1.0
·Reviewed Mar 23, 2020
Really general level concepts and does not go deep into the code of reinforcement models. The labs are scarce and not helpful at all.
M
Masa
1.0
·Reviewed Feb 22, 2020
I do not recommend this course to my friends.
Exercises are not prepared to help learners to understand ML for Trading.
C
Colin
3.0
·Reviewed Mar 1, 2020
It was ... OK. The lectures by the NYIF guy were immediately relevant to me, worth taking the course for. They should just have removed the Google stuff entirely and just started with an assumption of a basic knowledge of ML - just focus on the financial applications. So, bottom line: the good content is good, but mixed with a bunch of generic, time-wasting junk... that at least can be skipped over.
J
Jonathan
3.0
·Reviewed Jul 6, 2020
Very unusual course. Some useful theory on RL but very little practical coded examples of RL for trading. Heavy on pushing Google cloud services.
A
Abhinandan
3.0
·Reviewed Apr 16, 2020
This course seemed like movie trailer where there many jargons are introduced which are definitely worth but the information on the same is very limited which does not make students comfortable.
This course was more towards introducing the facility in Google Cloud than on the Title of the course.
V
Vlasov
2.0
·Reviewed Feb 18, 2021
If you expect to find a working example of RL trading bot using some exchange API and executing orders and so on - you won't find any. The part on RL algos is good (assuming you have good fundamental preparation on RL). But the examples are NOT from trading - good ole CartOpole... The part on trading is just on general theory of market risk, and not on RL trading. Don't waste your time on this course
J
Josef
3.0
·Reviewed Jul 10, 2020
The content was not bad, however it was really oriented towards promotion of GCP services.
Also, there was no tutorial how to really develop a strategy with reinforcement learning ( only few advices).
C
Chaojun
2.0
·Reviewed May 17, 2020
No practical, and useless for people who only wants more details about implementation of RL algo in trading rather than details about GCP.
P
Paolo
3.0
·Reviewed Jul 17, 2021
I've given a rating of 3 to this course because even it gives you an intuitive understanding of Reinforcement learning, it won't make you build your own RL agent in a trading environment, which is bad because you should be able to apply the theory that is thaught to you. That would give you even a deeper and more practical understanding of the subject.
The most interesting part of this course, even if it was treated lightly, is the "Investment and Trading Portfolio Optimization". Of course, you could deepen the subjects that are taught in this part, but I would have liked it to have been dealt with more thoroughly.
M
Mike
5.0
·Reviewed Mar 6, 2020
It was easy to follow but not easy. I learned a lot and I now have the confidence to implement Reinforcement learning to my own FX trading strategies. Thank you so much.
G
Grigoriy
5.0
·Reviewed Mar 7, 2020
Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn
M
Manfred
4.0
·Reviewed Mar 8, 2020
I learned new perspectives of trading - great
A
Amos
1.0
·Reviewed Jun 27, 2021
I went through the first two classes in this specialization to get to the reinforcement learning material. Total waste of time. The RL material consists of an introduction to RL in general, and some pre-done notebooks that execute RL on ai gym. None of it has anything to do with trading strategies. The finance lectures, of course, do relate to trading strategies, but they're just advice - it's all "do x, don't do y," with no explanation of *how* to do x or avoid doing y.
B
Biagio
1.0
·Reviewed May 30, 2020
Most of the course is a generic lecture about RL and LSTM taken from other courses. The rest is mostly advertisement for GoogleCloud, which it is not useful since you could do all exercises on a local laptop. Only a fraction of the course talks about finance and it is so generic that cannot be applied to any real world case.
V
Valdis
1.0
·Reviewed Oct 24, 2020
The learning curve is broken. It's like teach you 1+1=2 first, then you need to do calculus yourself, and lecturer say "see, it's easy" and move on to deep neural network now......
J
Jeremy
1.0
·Reviewed Oct 23, 2023
Cannot understand the girl in https://www.coursera.org/learn/trading-strategies-reinforcement-learning. Had to leave on subtitles. Very distracting.
J
Javier
1.0
·Reviewed Jul 10, 2024
Google Cloud Content is outdated, instructions are all wrong.