PROFESSIONAL EDUCATION
Leverage data-driven analysis to identify relevant financial trends.
Apply basic concepts of statistics and probability to finance
Understand what exploratory data analysis is and how to perform it with Python and Pandas
Engineer new features and functions from existing data
Comprehend how unsupervised machine learning models work and when they can be useful
Use simulation to solve portfolio risk and allocation problems and answer financial questions
Earn a credential certified by the University of Chicago and become part of the UChicago network
Data Science Educator and Curriculum Writer
Financial analysts and consultants who want to explore tech-driven data collection and analysis
Investors and venture capital and portfolio managers exploring ways to manage investment fund risk
CFOs and other managers who want to bolster financial data analysis in their organizations
Other finance professionals seeking technological tools and techniques to achieve their goals
Data professionals who want to develop a career in the financial industry or in a finance-oriented role
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