Below are curriculums that I’ve developed for machine learning and data science audiences.

Data Science Miniclass on Bootstrapping

This short class outlines the bootstrapping method with an associated Jupyter notebook to provide example code. It can be run using Binder to launch a cloud instance of a Jupyter notebook.

Intermediate Python: Machine Learning

As part of Stanford’s Software Carpentry program, I developed this intermediate Python course to provide learner’s a path past the core Software Carpentry curriculum. This short programme provides an introduction to unsupervised and supervised learning using scikit-learn.

Introduction to Unix Shell (with a mystery story)

For a Software Carpentry program, I created this version of their core Unix Shell program which uses a mystery narrative to engage the learners. The learners must learn and use their Unix skills to explore the contents of a fictional computer to solve the mystery of a missing person. It introduces core navigation, file interaction, and search skills.