Machine Learning for Financial Engineering. 3 credits

Catalog description

This course focuses on the intersection of machine learning (ML) and financial engineering. It will introduce both supervised and unsupervised learning techniques and their applications to key areas in finance, including risk management, algorithmic trading, and portfolio optimization. Special attention is given to the use of neural networks, deep learning, and reinforcement learning to solve complex financial problems, bridging the gap between predictive analytics and economic theory. Through a combination of theoretical discussions and hand-on practical projects, students will learn to leverage ML algorithms for data-driven decision-making in finance, equipping them with the skills to innovate and excel in the fast-evolving financial industry. Offered by Systems Engr & Operations Rsch . May not be repeated for credit. Equivalent to SYST 638 .