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About the Course
Our eight-week Machine Learning for Finance course focuses on collecting, organizing, and using data to perform advanced financial analysis with algorithms and statistical techniques and tools. During the course, you will have an opportunity to work through real-life case studies and examples giving you an opportunity to practically apply the theory you will learn to financial models.
You Will Learn To:
- Review statistics and probability to apply to finance
- Understand what linear regression is and when to use it, as well as how to apply linear regression metrics to a model
- Make models more rigorous by adding things like train/test split and cross-validation
- Backtest a model and understand why this is particularly important for finance
- Use simulation to solve a portfolio allocation problem
- Converse at a high level about several advanced topics in financial machine learning
- Understand and review statistics and probability
- Perform Exploratory Data Analysis in Python/Pandas
- Monitor a model for performance
- Define risk in finance
is the average annual base pay for a financial analyst in the United States.
is the anticipated value of the financial analytics market by 2030.
is the projected CAGR of the financial analytics industry from 2022 to 2030.
Meet Your Instructors
Lara Kattan, MPP
Data Science Educator and Curriculum Writer
Lara Kattan teaches for the University of Chicago Booth School of Business and data science learning platforms. Previously, she was a consultant at McKinsey and EY. She has an MPP in public policy
with a concentration in econometrics from UChicago.
Do you have questions?
The University of Chicago Approach to Online Learning
Our online learning programs are crafted with your specific needs in mind. Programs combine e-learning with live, interactive sessions to strengthen your skill set while maximizing your time. We couple academic theory and business knowledge with practical, real-world application. Through online learning sessions, you will have an opportunity to grow your professional network and interact with University of Chicago instructors and your classmates.