This course is part of the Machine Learning for Trading Specialization

3.6
stars
204 ratings

Jack Farmer

14,063 already enrolled

Offered By

New York Institute of Finance

Google Cloud

Machine Learning for Trading SpecializationNew York Institute of Finance

About this Course

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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).

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Course 3 of 3 in the

Machine Learning for Trading Specialization

Intermediate Level

Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.

Approx. 12 hours to complete

English

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What you will learn

Understand the structure and techniques used in reinforcement learning (RL) strategies.
Understand the benefits of using RL vs. other learning methods.
Describe the steps required to develop and test an RL trading strategy.
Describe the methods used to optimize an RL trading strategy.

Skills you will gain

Reinforcement Learning Model Development
Reinforcement Learning Trading Algorithm Optimization
Reinforcement Learning Trading Strategy Development
Reinforcement Learning Trading Algo Development

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 3 of 3 in the

Machine Learning for Trading Specialization

Intermediate Level

Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.

Approx. 12 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.03/5 (30 Ratings)

Jack Farmer

Curriculum Director

New York Institute of Finance

84,040 Learners

13 Courses

Offered by

New York Institute of Finance

The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders and offers a range of program delivery options, including self-study, online courses, and in-person classes. Its US customers include the SEC, the Treasury, Morgan Stanley, Bank of America and most leading worldwide banks.

Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Introduction to Course and Reinforcement Learning

In this module, reinforcement learning is introduced at a high level. The history and evolution of reinforcement learning is presented, including key concepts like value and policy iteration. Also, the benefits and examples of using reinforcement learning in trading strategies is described. We also introduce LSTM and AutoML as additional tools in your toolkit to use in implementing trading strategies.

3 hours to complete

10 videos (Total 64 min), 1 reading, 1 quiz

Week2

Week 2

5 hours to complete

Neural Network Based Reinforcement Learning

5 hours to complete

9 videos (Total 39 min)

Week3

Week 3

4 hours to complete

Portfolio Optimization

4 hours to complete

10 videos (Total 54 min)

Reviews

3.6

59 reviews

5 stars
34.14%
4 stars
25.36%
3 stars
20%
2 stars
7.80%
1 star
12.68%

TOP REVIEWS FROM REINFORCEMENT LEARNING FOR TRADING STRATEGIES

by GYJul 1, 2022

I look forward to examples of integration of decision based on reinforcement learning and algo-trading logic

by MLJul 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.

by JMJul 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

by SFMar 14, 2020

Good course introducing concepts in RL. Wish course provided more examples of using RL in stock prediction.

View all reviews

About the Machine Learning for Trading Specialization

This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies. By the end of the Specialization, you'll understand how to use the capabilities of Google Cloud to develop and deploy serverless, scalable, deep learning, and reinforcement learning models to create trading strategies that can update and train themselves. As a challenge, you're invited to apply the concepts of Reinforcement Learning to use cases in Trading. This program is intended for those who have an understanding of the foundations of Machine Learning at an intermediate level. To successfully complete the exercises within the program, you should have advanced competency in Python programming and familiarity with pertinent libraries for Machine Learning, such as Scikit-Learn, StatsModels, and Pandas; a solid background in ML and statistics (including regression, classification, and basic statistical concepts) and basic knowledge of financial markets (equities, bonds, derivatives, market structure, and hedging). Experience with SQL is recommended.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Reinforcement Learning for Trading Strategies

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