Machine Learning and Reinforcement Learning in Finance
Online
Format: Specialization – 4 months
Summary
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
Presented in partnership with Coursea