QBS 177/MATH 177: Methods of Statistical Learning for Big Data

Course Directors: Dr. Jiang Gui & Dr. Eugene Demidenko

  • Course description: This course provides an introduction to algorithms used in data science with applications to biomedical and health data science. The goal of this course is to present an overview of many of the approaches used for big data focusing on analytical methods and algorithms. The course assumes that students have some knowledge of R. Students will be provided with 2 large data sets. Lectures on data reduction, classification, and optimization will request students complete homework for these datasets. Special attention will be given to students’ active learning by programming in a statistical software package R. 
  • Prerequisites:
    • Coursework: QBS 149/QBS 120 and QBS 121. OR instructor permission.
    • Programming: Basic proficiency in R.

Syllabus