R

This workshop introduces the basic concepts of Deep Learning — the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels.

It is said that 80% of data analysis is spent on the process of cleaning and preparing the data for exploration, visualization, and analysis. This R workshop will introduce the dplyr and tidyr packages to make data wrangling and manipulation easier. Participants will learn how to use these packages to subset and reshape data sets, do calculations across groups of data, clean data, and other useful tasks.

This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.

This as an in-person ONLY workshop (no hybrid option). This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures.