Program Overview

Certificate in Financial Engineering

The Certificate in Financial Engineering is designed to equip students with the skills and knowledge required to succeed in the field of financial engineering. This program is particularly relevant as South Florida becomes a hub for next-generation investment firms, leading to an increased demand for financial engineers skilled in machine learning and data-driven analysis.

Program Details

• Availability: Coming Summer 2025
• Dates and Times: To Be Confirmed (TBC)
• Location: Hybrid: in-person and online

Program Objectives

The program aims to provide students with a comprehensive understanding of the fundamentals of finance-applied machine learning, enabling them to address common finance challenges such as financial forecasting and portfolio optimization. Upon completion of the program, students will be able to drive positive change in their organizations.

Curriculum

The program covers a range of topics, including:

• Supervised and unsupervised learning with an introduction to machine learning
• Fundamentals of Python and its application in data analysis for finance
• Hands-on experience in classification algorithms
• Model assessment and selection for better financial decision-making
• Microstructure, technical analysis, and algorithmic trading in the finance industry
• Feature importance, model calibration, and backtesting for financial model accuracy
• Portfolio optimization and factor models for maximum returns
• Deep learning and its applications in financial forecasting

Faculty

The program is taught by a leading scholar in machine learning and algorithmic trading, German G. Creamer. Dr. Creamer is an Associate Professor of quantitative finance and business analytics at Stevens Institute of Technology and an adjunct associate professor at Columbia University. He has extensive experience in the field, having worked as a senior manager in the Risk, Information, and Banking Division for American Express, and as an economic advisor to the president of Ecuador and the government of Equatorial Guinea.

Tuition

The program fee is $850 per participant for in-person attendance and $750 per virtual participant. Limited spots are available.

Program Structure

The program is designed to provide students with a comprehensive understanding of financial engineering, with a focus on machine learning and data-driven analysis. The curriculum is structured to equip students with the skills and knowledge required to succeed in the field, including hands-on experience in classification algorithms and model assessment and selection. The program is taught by a leading expert in the field, ensuring that students receive the highest quality education and training.