Machine Learning and Reinforcement Learning in Finance Specialization (NYU)

Colleagues, the Machine Learning and Reinforcement Learning in Finance Specialization from New York University equips you to compare ML for Finance with ML in Technology (image and speech recognition, robotics, etc.) , describe linear regression and classification models and methods of their evaluation, explain how Reinforcement Learning is used for stock trading , and learn approaches to modeling market frictions and feedback effects for option trading.. Build high-demand skills in Predictive Modelling, Financial Engineering, Machine Learning, Tensorflow, Reinforcement Learning, Option pricing and risk management, Simple model for market dynamics, Q-learning using financial problems, Optimal trading, and Portfolio Optimization. Skill-based training modules include: 1) Machine Learning in Finance - Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course,, 2) Fundamentals of Machine Learning in Finance - solve practical ML-amenable problems that they may encounter in real life that include: understanding where the problem one faces lands on a general landscape of available ML methods,  understanding which particular ML approach(es) would be most appropriate for resolving the problem, and ability to successfully implement a solution, and assess its performance., 3) Reinforcement Learning in Finance - fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management.Use reinforcement learning to solve classical problems of Finance such as portfolio optimization, optimal trading, and option pricing and risk management. Practice on valuable examples such as famous Q-learning using financial problems, and 4) Advanced Methods of Reinforcement Learning in Finance - explore links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles and potential applications of Reinforcement Learning for high-frequency trading, cryptocurrencies, and peer-to-peer lending.

Enroll today (individuals & teams welcome): https://tinyurl.com/x9zyn679 

Much career success, Lawrence E. Wilson - Financial Certification Academy