Non-SOT Event: Machine Learning Boot Camp: Analyzing Biomedical and Health Data

The Machine Learning Boot Camp is a two-day intensive boot camp of seminars combined with hands-on R labs and data applications to provide an overview of statistical concepts, techniques, and data analysis methods with applications in biomedical research.

By the end of the boot camp, participants will be familiar with the following topics:
- Penalized Regression Methods (Ridge and Lasso)
- Classification Models
- Tree Based Methods (Decision/Regression Trees)
- Clustering Algorithms
- Principal Component Analysis (PCA)

Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.

Prerequisites and Requirements: There are three requirements to attend this training:
- Each participant must have an introductory background in statistics (i.e., linear and logistic regression).
- Each participant must be familiar with R. The main platform used for the workshop will be RStudio Cloud, therefore we strongly recommend that participants have an intermediary understanding of R/RStudio prior to attending the Training.
- Each participant is required to have a personal laptop and a free, basic RStudio Cloud account prior to the first day of the workshop. All lab sessions will be done on this platform.

Capacity is limited. Paid registration is required to attend.

Additional Information:
- See website for more details: https://www.publichealth.columbia.edu/academics/non-degree-special-programs/professional-non-degree-programs/skills-health-research-professionals-sharp-training/trainings/machine-learning
- Email us with any questions: Columbia.MachineLearning@gmail.com