- Reinforcement Learning
- Portfolio Risk
- Risk Management
- Recurrent Neural Networks (RNNs)
- Artificial Neural Networks
- Applied Machine Learning
- Markov Model
- Financial Trading
- Portfolio Management
- Deep Learning
- Time Series Analysis and Forecasting
- Financial Market
Reinforcement Learning for Trading Strategies
Completed by Manuel García Ramírez
August 26, 2020
12 hours (approximately)
Manuel García Ramírez 's account is verified. Coursera certifies their successful completion of Reinforcement Learning for Trading Strategies
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
