Building on the Statistical Analysis for Health Data course, this course presents an overview of the basic concepts and techniques in predictive analytics as applied to health data. Techniques covered in this course include decision trees, classification rules, association rules, clustering, support vector machines, instance-based learning. Examples and cases are discussed to gain hands-on experience.
Thursday, March 13 - April 24: 6:30 p.m. - 9:30 p.m. (Virtual)
Location:
ONLINE
Instructor:
Muhammad Shahid
Notes:
This is a professional development; non-credit course. This course is offered as a virtual classroom with classes held, as per the scheduled day/time. Classes will be held online, using a combination of synchronous, real-time, instructor led sessions, supplemented with asynchronous activities. You should expect to attend class at the same time, each week, although not every session will be a full 3 hours of live instruction. Rather, classes will provide learners the opportunity to apply what has been covered by your course facilitator. Participants must bring a laptop to the class.
