Courses Taught by Hyun Min Kang

BIOSTAT607: Basic Computing for Data Analytics

  • Graduate level
  • Fall term(s)
  • 1-3 Credit Hour(s)
  • Instructor(s): Kang, Hyun Min
  • Prerequisites: No other courses
  • Advisory Prerequisites: students with no prior programming experience at all are strongly encouraged to take BIOSTAT606 “Introduction to Biocomputing” offered before the Fall term starts.
  • Description: This course is designed as a 3-credit modular course focusing on basic programming skills, including Python (1 credit), R (1 credit), and C++ (1 credit). The course covers key features of each programming language, data structures, basic data processing skills, basic data visualization skills (for Python and R), and basic UNIX skills. Students are allowed to take one or more modules according to the need basis.
  • Course Goals: The goal of this modular course is to prepare students in Health Data Science program with adequate programming skills. It serves as a prerequisite of several other courses in the Health Data Science Concentration program.
  • Competencies: (a) Apply basic informatics techniques with vital statistics and public health records in the description of public health characteristics and in public health research and evaluation. (b) Master computing software to perform biomedical and health data analyses. (c) Interpret results of statistical analyses found in public health studies.
  • Learning Objectives: (a) To understand key features of R, python, and C++ programming languages in a modular way. (b) To understand basic data structures, basic data processing skills, basic data visualization skills (for Python and R modules), and basic UNIX skills

BIOSTAT625: Computing with Big Data

  • Graduate level
  • Fall term(s)
  • 3 Credit Hour(s)
  • Instructor(s): Jiang, Hui Kang, Hyun Min
  • Prerequisites: R module in BIOSTAT 607 or equivalent.
  • Description: This course will cover techniques for computing with big data. The topics include programming, data processing, debugging, profiling and optimization, version control, software development, interfacing with databases, interfacing between programming languages, visualization, high performance and cloud computing. Hands-on experience will be emphasized in lectures, homework assignments and projects.
  • Course Goals: This course prepares the students with techniques for manipulating and processing big data by writing customized computer programs. It builds the foundation for the computing aspects of data science. After taking this class, students are expected to have a practical understanding of important computing issues for health big data analysis.
  • Competencies: (a) Apply basic informatics techniques with vital statistics and public health records in the description of public health characteristics and in public health research and evaluation. (b) Master computing software to perform biomedical and health data analyses. (c) Interpret results of statistical analyses found in public health studies.
  • Learning Objectives: (a) To master techniques for manipulating and processing big data by writing customized computer programs. (b) To understand the foundation for the computing aspects of data science. (c) To have a practical understanding of important computing issues for health big data analysis.

BIOSTAT815: Advanced Topics in Computational Statistics

  • Graduate level
  • Winter term(s)
  • 3 Credit Hour(s)
  • Instructor(s): Kang, Hyun Min
  • Prerequisites: BIOSTAT601, BIOSTAT602 and BIOSTAT615 or equiv and proficiency in C++ and R
  • Description: Modern numerical analysis for statisticians. Combination of theory and practical computational examples illustrating the current trends in numerical analysis relevant to probability and statistics. Topics choose from numerical linear algebra, optimization theory, quadrature methods, splines, and Markov chains. Emphasis on newer techniques such as quasi-random methods of integration, the EM algorithm and its variants, and hidden Markov chains. Applications as time permits to areas such as genetic and medical imaging.
  • Syllabus for BIOSTAT815