Big Data and Machine Learning in Health Care Applications

Harvard Extension School

CSCI E-87

Section 1

CRN 17070

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While large volumes of digital health-care data have been captured for decades, we are only starting to mine them for information that can significantly advance health care delivery and quality. Built from many practical experiences, this course teaches students how to apply big data analytics and machine learning to the most challenging problems found in modern hospitals. We cover several important areas—operational, clinical, and imaging—using hands-on examples and real problems. Students not only learn how to build efficient data models, but also how to implement them in different health-care environments, avoiding the most common pitfalls and achieving meaningful results.

Registration Closes: August 28, 2025
Credits: 4

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Term

Fall Term 2025

Part of Term

Full Term

Format

Live Attendance Web Conference

Credit Status

Graduate, Noncredit, Undergraduate

Section Status

Open

Instructor Info

Oleg Pianykh, PhD

Assistant Professor of Radiology, Harvard Medical School, and Director of Medical Analytics, Massachusetts General Hospital


Meeting Info

Th 5:10pm - 7:10pm (9/2 - 12/20)

Participation Option: Online Synchronous

Deadlines

Last day to register: August 28, 2025

Additional Time Commitments

Optional sections to be arranged.

Prerequisites

Basic understanding of statistics and machine learning. Programming in Python or Matlab is required for most homework assignments.

Notes

This course meets via web conference. Students must attend and participate at the scheduled meeting time. See minimum technology requirements.

Tuition

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All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
17070 1 Online Synchronous Oleg Pianykh Open Th 5:10pm - 7:10pm
 Sep 2 to Dec 20

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