Workshops, Curriculum, and Tutorials


I am a big proponent of making educational material I create freely available. I encourage the use of these materials for self-taught learning and to used and remixed for others to use for their own teaching. Topics range from statistical analysis, modeling, cloud computing, machine learning, biology, data management, computational reproducibility, and general R & Python programming.


  • Talk and workshop on using biodiversity and natural history museum databases - This is a talk and workshop that focuses on introducing R users to natural history and biodiversity databases, we further work through an exploratory analysis in R using the Neotoma database.
  • Curiositydata.org - This website includes many tutorials using biodiversity and ecological data. The types of analysis are wide ranging, using data such as dinosaur fossils, 3D ct-Scans, Google Earth fire data, animal movement data and more. Tutorials go through data retrieval, data cleaning, exploratory analysis and data cleaning. These works were written by myself, contributors, and a team of UC Berkeley undergraduate interns that I led during the 2018/2019 school year.
  • The Data Science of Shape Using Momocs - This tutorial explores using the Momocs R package for doing 2D morphometric analysis.
  • How to Fully Explore Your Clustering Results using ggplot and kohonen R packages - This tutorial using the Titanic Survival dataset as a basis to learn clustering using Self Organizing Maps (SOM). The focus is on how to visualize the results to ensure full understanding behind the clustering algorithm.
  • Using AWS for Neural Networks - This documentation was written for my research team to build Neural Networks on Amazon Web Services.
  • MACS2 to explore ChIP-Seq data - This lessson was bulilt and taught when I TAd a Genomics course (BIS180L) at UC Davis with Julin Maloof.
  • Become a Superhero, handle your data with R: This is a beginner R course aimed at learners with no programming experience. I originally wrote this course for high schools, but has been used in several undergraduate and graduate courses over the years. I wrote it when I first started using R, so has some very valuable insights conceptual knowledge that is usually glossed over in other tutorials. Warning: It was written before tidyverse and before the Rstudio environment was so widespread.
  • Evo Devo Module - This class is about my favorite field of biology - evolutionary development, often nicknamed Evo Devo. It is a lecture and lab that can be taught in about a three hour period. The lab uses fresh cut flowers to explore evo-devo concepts and plant evolutionary biology. I taught this lesson at three different colleges/universities.
  • Introduction to Git and GitHub - This was written and taught with Matthias Bussonnier for the Hacker Within group at UC Berkeley.
  • Gene Expression analysis Self Organizing Maps Tutorial: This tutorial was written for several research groups interested in using Self Organizing Maps (SOM) for gene expression analysis. The benefit of using SOM clustering, as opposed to other clustering algorithms for gene expression analysis, is that you can constrain clustering based on many variables, such as genotype.
  • Reproducible Research Version Control Lesson for Data Carpentry - This lesson teaches the concept of version control using git. The lesson begins with a slides describing the motivations for using version control and Github. The first activity is a follow along partner activity which explores git in GitHub only (02-git-in-github). Since the project is never brought locally onto the students computer, the students do not need to install git for this project. The second activity starts with a demo in RStudio which can be followed along if the students have installed git (03-git-in-rstudio). This activity introduces the students to using git on their computers.
  • Tutorial on Mixed effect Linear Modeling - This is a tutorial on how to analyze data with Mixed Effect Linear Modeling in R using the lme4 R package that I co-opted from Dan Chitwood.
  • Reproducible Science Workshop on Tools, Resources, and Practices
  • Reproducible Research Organization Lesson - Full workshop that I co-wrote and co-taught on two occasions.
  • Ropensci Reproducibility Guide - A project I led and built with other contributers at the first Ropensci Hackathon.
  • BIS180 L - This is a wonderful course designed by Julin Maloof. I TAd this course when I was pursuing my PhD at UC Davis.