In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance.
This course is part of the Machine Learning and Reinforcement Learning in Finance Specialization
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New York University
New York University is a leading global institution for scholarship, teaching, and research. Based in New York City with campuses and sites in 14 additional major cities across the world, NYU embraces diversity among faculty, staff and students to ensure the highest caliber, most inclusive educational experience.
Syllabus - What you will learn from this course
Black-Scholes-Merton model, Physics and Reinforcement Learning
Reinforcement Learning for Optimal Trading and Market Modeling
Perception - Beyond Reinforcement Learning
Other Applications of Reinforcement Learning: P-2-P Lending, Cryptocurrency, etc.
Reviews
TOP REVIEWS FROM OVERVIEW OF ADVANCED METHODS OF REINFORCEMENT LEARNING IN FINANCE
Great refreshment on Stochastic calculus and overall rewind of the specialization!
It was very difficult to get the peer-graded assignments graded.
About the Machine Learning and Reinforcement Learning in Finance Specialization
The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance.

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