Machine Learning Techniques in Economics and Finance

Harvard Summer School

MGMT S-105

Section 1

CRN 35878

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This course covers machine learning techniques that can be applied to the fields of economics and finance. The techniques covered in this course include multiple linear regression, least absolute shrinkage and selection operator (LASSO), ridge regression, logistic regression, Naive Bayes, portfolio optimization, and unstructured learning techniques such as k-nearest neighbors (k-NN).

Credits: 4

Term

Summer Term 2026

Part of Term

3-week session II

Format

On Campus

Credit Status

Graduate

Section Status

Open

Instructor Info

Sudhakar Raju, PhD

Professor of Finance and Data Science, Rockhurst University

Meeting Info

MTWTh 6:30pm - 9:30pm (7/13 - 7/30)

Participation Option: On Campus

Deadlines

Last day to register:

Prerequisites

Prior knowledge of R. ECON S-110 is recommended.

Notes

Not open to Secondary School Program students.

Tuition

All Sections of this Course

CRN	Section #	Participation Option(s)	Instructor	Section Status	Meets	Term Dates
35878	1	On Campus	Sudhakar Raju	Open	MTWTh 6:30pm - 9:30pm	Jul 13 to Jul 30