High-Dimensional Statistics with R

This course is intended for those who have a working knowledge of statistics and linear models with R and wish to learn high-dimensional statistical methods with R.

This is a short course aimed at familiarising learners with statistical and computational methods for the extremely high-dimensional data commonly found in biomedical and health sciences (e.g., gene expression, DNA methylation, health records). These datasets can be challenging to approach, as they often contain many more features than observations, and it can be difficult to distinguish meaningful patterns from natural underlying variability. To this end, we will introduce and explain a range of methods and approaches to disentangle these patterns from natural variability. After completion of this course, learners will be able to understand, apply, and critically analyse a broad range of statistical methods. In particular, we focus on providing a strong grounding in high-dimensional regression, dimensionality reduction, and clustering.

Ed-DaSH

Ed-DaSH is a Data Science training programme for Health and Biosciences. The team has developed workshops using The Carpentries platform on the following topics. See workshops for dates and registration details. All workshops will be delivered remotely.