Machine Learning and Reinforcement Learning in Finance | NYU Tandon School of Engineering

Machine Learning and Reinforcement Learning in Finance


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Format: Specialization – 4 months


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.

Key Takeaways

  • Compare ML for Finance with ML in Technology (image and speech recognition, robotics, etc.)  
  • Describe linear regression and classification models and methods of their evaluation
  • Explain how Reinforcement Learning is used for stock trading  
  • Become familiar with popular approaches to modeling market frictions and feedback effects for option trading.

Who Should Attend

The specialization is designed for three categories of students:

  • Practitioners working at financial institutions such as banks, asset management firms or hedge funds
  • Individuals interested in applications of ML for personal day trading
  • Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance.

Course Outline

  • Course 1: Guided Tour of Machine Learning in Finance
  • Course 2: Fundamentals of Machine Learning in Finance
  • Course 3: Reinforcement Learning in Finance
  • Course 4: Overview of Advanced Methods of Reinforcement Learning in Finance

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