Machine Learning for Financial Modeling

Faculty: Igor Cialenco and Matthew Dixon

Format: Live, online classes

Structure: Six – two hour sessions over six weeks

Timeline: April 6, 2022 to April 21, 2022: Tuesdays and Thursdays 5:30-7:30 pm CT.

Machine learning has been a major catalyst for financial decision making with big data. From credit scoring in the financial services industry, to investment models for portfolio and wealth management, to algorithmic trading and risk management. It is well known that machine learning is often used to make basic decisions, such as loan approvals, but the field has advanced substantially in the last few years to deliver a much broader set of capabilities. The goal of this short-course is to equip finance professions with a better understanding of which specific techniques in machine learning are shaping the finance industry.

In particular, we address common questions such as “Why has machine learning replaced statistical modeling?” and “how is machine learning used for portfolio selection?”.  The overall format of the course will be oriented towards finance professionals who are key decision makers in their organizations. Real world applications of machine learning using big data shall be demonstrated in areas such as trading, investment, and risk management.  A key value proposition of this workshop will be providing frameworks to understand how to most effectively apply machine learning to financial workflows across a broad range of business functions and roles, from data capture through to modeling, risk management and reporting.

Fee:  $3,000 per person 

Discount is available for Illinois Tech alumni. Please email the Illinois Tech Office of Professional and Continuing Education at to get the promotion code.