Courses Details

BIOSTAT626: Machine Learning for Health Sciences

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Wen, William (Residential);
  • Prerequisites: BIOSTAT 601,BIOSTAT 602, BIOSTAT 650, BIOSTAT 651, BIOSTAT 607
  • Description: This is a 3-credit course introducing modern machine learning algorithms and data analytics for prediction, classification and data pattern recognition, with an emphasis on their applications in health data sciences.
  • Learning Objectives: (a) To understand the foundation and rules to use machine learning techniques for handling data from the health sciences (b) To develop practical knowledge and understanding of modern machine learning techniques for health big data analysis. (c) To learn and master basic software and programming skills to apply machine learning algorithms in analyzing data arising from the health sciences.
  • Syllabus for BIOSTAT626