DSC 510 Health Data Science

Casey Bennett

Office: CDM 373
Spring 2023-2024
Class number: 33347
Section number: 910
OLASY NCH00 Online Campus


This course focuses on how data science can be used in modern healthcare, including for clinical studies and public health.  Students will be introduced to a variety of healthcare data, such as electronic health records, payor data, genetic data, geospatial data, public health data, medical imaging, unstructured clinical notes, etc.  The class will discuss a variety of data science techniques to analyze and understand patterns in such data, including machine learning and other modeling techniques, as well as effectively communicating those results back to clinicians and patients.  Topics in the course will include healthcare-specific applications of the following: machine learning, data engineering, data visualization, computer vision, natural language processing (NLP), and human-computer interaction (HCI).  We will also cover fundamental data concepts in health, health data ethics, and the history of health data science.  The overarching aim of the course is for students to learn how to solve data science problems in the health sector.

Course Learning Goals

At the end of the course, students should be able to:

  • understand how to solve data science problems that are specific to human health and healthcare
  • Understand the utility of different modeling methods for particular healthcare scenarios, and be able to choose/recommend the correct one
  • understand how we can apply machine learning to healthcare data, and the unique challenges that come along with that
  • know how to manage data in healthcare settings for analytical purposes, including application of data engineering principles
  • Understand how to utilize data visualization and HCI methods for communicating data science results to clinicians and patients
  • be able to explain the value of data science to non-technical audiences in healthcare (doctors, patients, caregivers, etc.)


Some basic knowledge of Python programming

School policies:

Changes to Syllabus

This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.

Online Course Evaluations

Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation. Students complete the evaluation online in CampusConnect.

Academic Integrity and Plagiarism

This course will be subject to the university's academic integrity policy. More information can be found at If you have any questions be sure to consult with your professor.

All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.

Academic Policies

All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at

Students with Disabilities

Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296