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
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.
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
Week
2

Week 2

5 hours to complete

Neural Network Based Reinforcement Learning

5 hours to complete
9 videos (Total 39 min)
Week
3

Week 3

4 hours to complete

Portfolio Optimization

4 hours to complete
10 videos (Total 54 min)

Reviews

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About the Machine Learning for Trading Specialization

Machine Learning for Trading

Frequently Asked Questions

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