Ementorhub

What you'll 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'll gain

Financial Market

Artificial Neural Networks

Deep Learning

Applied Machine Learning

Artificial Intelligence and Machine Learning (AI/ML)

Time Series Analysis and Forecasting

Financial Trading

Machine Learning Software

Reinforcement Learning

Machine Learning

Markov Model

Machine Learning Methods

Portfolio Management

There are 3 modules in this course

To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).

Neural Network Based Reinforcement Learning

Portfolio Optimization