- Applied Machine Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Recurrent Neural Networks (RNNs)
- Financial Market
- Risk Management
- Time Series Analysis and Forecasting
- Portfolio Risk
- Financial Trading
- Markov Model
- Deep Learning
- Artificial Neural Networks
- Portfolio Management
Reinforcement Learning for Trading Strategies
Completed by Klaus Christoph Wietzig
June 4, 2020
12 hours (approximately)
Klaus Christoph Wietzig'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
