Courses Taught by William Wen

BIOSTAT626: Machine Learning for Health Sciences

  • Graduate level
  • Winter term(s)
  • 3 Credit Hour(s)
  • Instructor(s): Wen, William
  • 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.

BIOSTAT680: Applications of Stochastic Processes I

  • Graduate level
  • Fall term(s)
  • 3 Credit Hour(s)
  • Instructor(s): Wen, William
  • Prerequisites: Biostat 601 and Math 450 or equiv
  • Description: Conditional distributions, probability generating functions, convolutions, discrete and continuous parameter, Markov chains, medical and health related applications.
  • Syllabus for BIOSTAT680