Teaching
Undergraduate Courses
MDSC 403: Computation for Bioinformatics. A mandatory course for undergraduate students in the Bachelor of Health Sciences program. Basic statistical models and their implementations in R. Basics of Linux command lines and high-performance computing (HPC) clusters will also be taught. (Every year since 2018)
MDSC 523: AI Applications in Health. Basic machine learning models and their applications in health data science. (Jointly with Dr. David Anderson. 2020 - 2023)
DATA 603: Statistical Modelling with Data. An introduction to multiple regression and ANOVA, including exposure to multivariate model selection, prediction, the statistical design of experiments. (2023)
Support vector machine
Neural network
Graduate Courses
MDSC 679: Foundations of Bioinformatics. A mandatory course for students in the Bioinformatics graduate program. Mainly for students with biological background to learn statistics and machine learning with a focus of their applications in genomic data analyses. (Jointly with Dr. Jason de Koning, 2018, 2020, 2021)
MDGE 612: Foundations of Machine Learning. A new 1-unit course equivalent to the machine learning components in MDSC 679 (that will be replaced by two 1-unit courses). 2023, 2024.
Ad hoc Courses
MDSC 755: Directed Study (Basics in Machine Learning). An ad hoc course for students of mine or my collaborators. It is a flexible class based on the background of students. The content may be basic mathematical and statistical models underlying machine learning. Or it can be hands-on practice using machine learning libraries such as PyTorch. (Whenever our graduate students request.)
