Reinforcement Learning by Udacity

In this course, learners will explore how to design, backtest, and optimize a working reinforcement-based ML trading strategy. This course will introduce popular techniques and indicators used in reinforcement learning-based trading, such as Q-learning, PCA, use of market indicators, assessment of market context, and assessment of the strategy outcomes. This course is designed for hobby traders with a background in data science. By the end of this course, you will be able to build, train, backtest, and optimize a reinforcement learning trading strategy with Python.