A Biostatistics Short Course
A six-week short course for researchers or students wanting to learn more about data science, machine learning, data visualization, and tools for reproducible research and team science. Three lectures provide an introduction to machine learning (ML) in
biomedical research, covering topics such as: differences between ML and classical statistical models, the basic steps for building and validating predictive models (“supervised ML”), tools for interpreting ML models, variable selection,
and “unsupervised ML” (e.g. “clustering methods” to derive patient subgroups, and principal component analysis for “dimension reduction”).
Tuesdays: 5:00 - 7:00 pm
Location: Virtual
Course Fee: $340 - A credit card can be used for payment or speedtype. To inquire about using a Speedtype, please contact CIDA.admin@CUAnschutz.edu.
Schedule of Topics
- Week 1 (10/10): Overview of Data Science
- Week 2 (10/17): Introduction of Machine Learning in Biomedical Research
- Week 3 (10/24): Clustering and Pattern Finding ("unsupervised" Machine Learning)
- Week 4 (10/31): Powerful Predictive Models and Variable Selection ("supervised" Machine Learning)
- Week 5 (11/07): Fundamentals of Data Visualization
- Week 6 (11/14): Reproducible Research and Team Science
Questions? Please contact BERD Program Manager.
Sponsored by the Biostatistics, Epidemiology and Research Design (BERD) core of the CCTSI.