Big Data and Machine Learning in Healthcare Applications

Harvard Extension School

CSCI E-87

Section 1

CRN 17070

View Course Details
While large volumes of digital healthcare data have been captured for decades, we are only starting to mine them for information that can significantly advance healthcare 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 healthcare environments, avoiding the most common pitfalls and achieving meaningful results.

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 (9/3 - 12/21)

Participation Option: Online Synchronous

Deadlines

Last day to register: August 29, 2024

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.

Syllabus

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 3 to Dec 21