|
|||
CLRES 2037 - PRACTICAL MACHINE LEARNING: APPLICATIONS IN CLINICAL RESEARCH USING STATISTICAL PACKAGESMinimum Credits: 1 Maximum Credits: 1 The aim of this course is to provide hands-on experience using statistical machine learning concepts and software to analyze real datasets. It is intended to be a partner course to CLRES 2035: Fundamentals of Machine Learning in Clinical Research, in order to provide an opportunity to further develop the skills and concepts explored there. We will first cover the basics of opening and exploring datasets in R and RStudio (both freeware). Then we will have one class dedicated to each of the topics covered in CLRES 2035. Students will either bring their own computers to class. The instructors will provide a set of instructions for the students to follow, usually involving R code, and the students and instructors will work through this code and discuss together. This includes actually running the code on students' designated machines, discussing the code's components, reviewing the output together, and interpretation. The course does not require advanced knowledge in mathematics or computer programming. All required concepts involving the execution of statistical software code will be learned as part of the course. Academic Career: Graduate Course Component: Lecture Grade Component: Grad LG/SNC Basis
|
|||
|
All catalogs © 2026 University of Pittsburgh. Powered by the Acalog™ Academic Catalog Management System™ (ACMS™).
|
|||