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Machine Learning for Finance

Leverage data-driven analysis to identify relevant financial trends.

Limited spots.

About the Course

The University of Chicago’s 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. You will engage with real-world case studies and examples, allowing you to apply the theory you will learn to financial models.

You Will Learn To:

  • Work with linear regression and apply linear regression metrics to a model.
  • Make models more rigorous by adding train/test split and cross-validation.
  • Backtest a model and understand why backtesting is important.
  • Use simulation to solve a portfolio allocation problem.
  • Converse at a high level about advanced topics in financial machine learning.

 

After successfully completing the course, you will receive a credential certified by the University of Chicago.

Methodologies and Techniques:

  • Pandas
  • Python

 

Request for Information
https://online.professional.uchicago.edu/info-typ/fnb-dfa-infotyp/

Career Outlook

$

74

K

The average annual base pay for a financial analyst in the United States.

Source: Glassdoor

$

43

B

The anticipated value of the financial analytics market by 2030.

Source: Global Market Insights

15

%

The projected CAGR of the financial analytics industry from 2022 to 2030.

Source: Global Market Insights

  • Accountant
  • Asset/Wealth Manager
  • CFO
  • Commercial Banker
  • Economist
  • Finance Manager
  • Financial Advisor
  • Financial Analyst
  • Investment Banker
 
 

Meet Your Instructor

These instructors teach this course regularly. Please speak to your enrollment advisor if you wish to know who the current teacher is.

instructor Lara Kattan

Lara Kattan, MPP

Data Science Educator and Curriculum Writer

Lara Kattan is a data scientist, risk professional, and curriculum developer. She is an adjunct assistant professor at the University of Chicago Booth School of Business and develops data science curriculums for several learning platforms. Previously, she was a consultant at McKinsey and EY.

Kattan has a master’s degree in public policy with a concentration in econometrics from the University of Chicago and a BA in economics and political science from Northwestern University.

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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.

What Our Participants Say

"This course is valuable for gaining further knowledge of ML content for finance. It enhanced my understanding of application principles and increased my confidence in my ability to make decisions related to problems that can be solved by applying the concepts covered."

"This course helped me refresh concepts, learn about new use cases, and bolster my capabilities as a leader in a company where we create AI solutions."

“By directly involving students in the challenge of securing the right data and exploring potential solutions, we’re equipping them with the foundational skills required to deliver tangible results to clients.”

Register Now

Are you ready to take a leap forward and immerse yourself in a new learning experience? Register online or schedule a call to request more information. Enroll now and gain valuable knowledge and skills that will boost your career to the next level.