This workshop is an introduction to the Julia programming language for people familiar R, Python, or MATLAB. Compared to those languages, Julia code typically runs orders of magnitude faster but has a similar level of abstraction, so you can focus on your research problem rather than hardware minutiae. Julia also provides out-of-the-box Unicode support, an easy-to-use package manager, multi-threading facilities, a macro system, and a rich type system to optimize and prevent bugs in your code. Workshop topics include a concise overview of Julia’s syntax and features, an end-to-end introduction to using built-in functions and contributed packages to read, summarize, and visualize tabular data, real-world examples where we’ve found Julia beneficial. After this workshop, learners will be able to describe Julia’s strengths and weaknesses relative to other programming languages and get started using Julia in their own research projects.

This workshop is NOT designed for entry level programmers. Learners must already be proficient in a language like R or Python. All learners will need access to an internet-connected computer with the latest versions of Zoom and Julia.

Prerequisites: Participants must be proficient programming in a high-level language such as R, Python, MATLAB, etc.. Before the workshop, participants must install the latest version of Julia on their computer (https://julialang.org/).

Instructors: Nick Ulle, UC Davis DataLab; Carl Stahmer, UC Davis DataLab; Derek Devnich, UC Merced Library; Ezra Morrison, UC Davis Biostatistics