Welcome to the Statistical Machine Short Course! This course is designed to introduce you to statistical machine learning and some data management with the popular statistical software R.
- Date: June 13th, 2023
- Location: HLTH B450 (Health Science Building, B Wing)
The one-day course is led by Dr. Li Xing, Assistant Professor at the Department of Mathematics and Statistics at the University of Saskatchewan. Dr. Xing has extensive experience in statistical machine learning and has worked on developing novel statistical tools for complex data, particularly in genomics and experimental design for observational studies and clinical trials. You can find more information about Dr. Xing on her website: https://ubclxing.github.io/.
- 9:30 am-11:00 am: Knowledge Lecture on Introduction to Statistical Machine Learning, Linear Regression and Logistic Regression by Dr. Xing
- 11:10 am-11:30 am: R Lecture on R/Rstudio Installation, R Introduction and Data Management by Ms. Lina Li (TA)
- 1:00 pm-1:30 pm: R Lecture on Linear and Logistic Regression by Mr. Kyle Gardiner (TA)
- 1:30 pm-2:00 pm: Hand-on Practice Session on R/Rstudio installation + Introduction + Data Management
- TA: Lina Li
- Tutors: Kyle Gardiner and Jing Wang
- 2:00 pm-2:30 pm: Hand-on Practice Session on Linear and Logistic Regressions with R
- TA: Kyle Gardiner
- Tutors: Lina Li and Jing Wang
- 3:00 pm-3:50 pm: Knowlege Lecture on Penalized Regressions by Dr. Xing
- 3:50 pm-4:10 pm: R Lecture on Penalized Regressions by Kyle Gardiner(TA)
- 4:10 pm-4:30 pm: Hand-on Practice Session on Penalized Regressions
- TA: Kyle Gardiner
- Tutors: Lina Li and Jing Wang
Please note that a laptop is required for all the hands-on sessions. All materials will be provided through GitHub links before the start of each session. Please install R and Rstudio before this workshop. Instructions for the installation are in the Session 1 folder.
We hope this short course could inspire your interest in learning statistical machine learning. We look forward to seeing you here!