- Artificial Intelligence and Machine Learning (AI/ML)
- Financial Trading
- Financial Market
- Reinforcement Learning
- Recurrent Neural Networks (RNNs)
- Time Series Analysis and Forecasting
- Markov Model
- Portfolio Management
- Artificial Neural Networks
- Deep Learning
- Applied Machine Learning
- Risk Management
Reinforcement Learning for Trading Strategies
Completed by Kritsana Uttamang
June 6, 2021
12 hours (approximately)
Kritsana Uttamang'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
