About this Course

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Intermediate Level

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

Approx. 12 hours to complete
English

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 DevelopmentReinforcement Learning Trading Algorithm OptimizationReinforcement Learning Trading Strategy DevelopmentReinforcement Learning Trading Algo Development
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

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

Approx. 12 hours to complete
English

Offered by

Placeholder

New York Institute of Finance

Placeholder

Google Cloud

Syllabus - What you will learn from this course

Week
1

Week 1

3 hours to complete

Introduction to Course and Reinforcement Learning

3 hours to complete
10 videos (Total 64 min), 1 reading, 1 quiz
10 videos
What is Reinforcement Learning?9m
History Overview2m
Value Iteration9m
Policy Iteration6m
TD Learning8m
Q Learning6m
Benefits of Reinforcement Learning in Your Trading Strategy6m
DRL Advantages for Strategy Efficiency and Performance7m
Introduction to Qwiklabs3m
1 reading
Idiosyncrasies and challenges of data driven learning in electronic trading10m
Week
2

Week 2

5 hours to complete

Neural Network Based Reinforcement Learning

5 hours to complete
9 videos (Total 39 min)
9 videos
Deep Q Networks - Loss2m
Deep Q Networks Memory2m
Deep Q Networks - Code3m
Policy Gradients4m
Actor-Critic3m
What is LSTM?7m
More on LSTM4m
Applying LSTM to Time Series Data7m
Week
3

Week 3

4 hours to complete

Portfolio Optimization

4 hours to complete
10 videos (Total 54 min)
10 videos
Steps Required to Develop a DRL Strategy7m
Final Checks Before Going Live with Your Strategy5m
Investment and Trading Risk Management4m
Trading Strategy Risk Management4m
Portfolio Risk Reduction4m
Why AutoML?13m
AutoML Vision2m
AutoML NLP3m
AutoML Tables7m

Reviews

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About the Machine Learning for Trading Specialization

Machine Learning for Trading

Frequently Asked Questions

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