46-892 Data Analytics in Finance

6 units, Carnegie Mellon University

The course covers methods of extracting useful information from raw financial data. Focus is placed on methods of data exploration and mining, with particular emphasis on handling large and complex financial data sets. Topics include understanding how to use nonparametric density estimation and smoothing to fit to data with minimal assumptions. We will also explore how to implement methods of unsupervised learning such as principal components analysis and nonlinear dimension reduction and understand how these approaches can yield useful representations and insights.

Prerequisites: none listed

Offered: Spring 2027, Summer 2026, Spring 2026

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