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
The copyright on
this video is owned by the Regents of the University of California and is
licensed for reuse under the Creative Commons Attribution 4.0 International (CC
BY 4.0) License.