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Machine Learning for Finance

Collect, organize, and use data to perform advanced financial analysis with algorithms and statistical techniques and tools.
  • September 19, 2022.
  • Online learning with live, interactive sessions
  • USD $2,500
  • English, Portuguese, and Spanish
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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 be taught to financial models.

You Will Learn To:

  • Review statistics and probability, and to apply basic concepts of statistics 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.
You Will Be Able To:
  • Understand and review statistics and probability.
  • Perform Exploratory Data Analysis in Python/Pandas.
  • Monitor a model for performance.
  • Define risk in finance.

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Career Outlook

$

72

k

The average annual base pay for a financial analyst in the US

$11B

The anticipated size of the financial analytics market by 2026

11.2%

The projected CAGR of the industry from 2021 to 2026

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

Meet Your Instructors

Headshot of the certificate instructor: Lara Kattan
Lara Kattan, MPP
Machine Learning for Finance

Lara Kattan is a data science educator and curriculum writer. She is currently developing curriculum for institutions such as the University of Chicago and data science learning startups. Prior to embarking on a career in curriculum development, she was a consultant in risk practice at McKinsey & Co. She has an MA in public policy with a concentration in econometrics from the University of Chicago and a BA in economics and political science from Northwestern. Kattan is a lifelong learner and is pursuing an MA in computer science and another in mathematics from DePaul University.

University of Chicago

“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.”

– Greg Green, PhD, Associate Senior Instructional Professor and Director of the MScA Program at the University of Chicago

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.

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Gain valuable knowledge and skills that will
boost your career to the next level.

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