Data Mining for Healthcare Analytics
The proliferation of data in the post-EHR era creates opportunities for large-scale data analysis to discover meaningful patterns and trends. Through interactive, online learning, explore the application of data mining techniques for purposes of big data analytics using administrative and clinical systems data. Gain an overview of the data mining process, data mining standards and output protocols, and common techniques used in mining healthcare data. By the end of this course, students will be familiar with data mining techniques and visual representation methods that increase understanding of complex data.
Learning Outcomes
- Define and examine the objectives of data mining
- Illustrate the ability to observe, manipulate and chart data
- Explain when to use each contract type
- Apply appropriate data mining methods to data sets
- Execute a data mining project
Skills You Will Gain
- Data mining techniques and standards
- Data mining preparation
- Data visualization and reporting
*In order to utilize all course tools, students need access to a PC. Students with Mac computers can take and complete the course but will not gain as much hands-on experience.
Section Notes
Course begins July 5 and ends September 13. This class will conduct one mandatory Saturday synchronous video session toward the end of the course, so please plan accordingly.
This is not a self-paced course. Students will progress through the course together. Course modules are released weekly, where lessons typically load on Sundays and are due the following Saturdays. You can log in and work on courses at any time within that week to view lectures and complete assignments. The previous week's lesson will remain available for the duration of the course. If you enroll after the course start date, you will need to contact the instructor regarding missed lessons.
This is the last time this course will be offered. If you do not complete this course this quarter, there will not be an option to transfer to a later quarter.
Refund Deadline: July 19, 2023. Refunds and/or enrollment transfers will not be approved after this date.
Enrollment Policies
View complete enrollment policy information including details on withdrawals and transfers.
Refund Deadline: July 19, 2023. Refunds and/or enrollment transfers will not be approved after this date.
Prerequisites
Candidates for the certificate are expected to have prior professional experience in a healthcare setting and familiarity with statistics.