Date Oct 13, 2022, 2:30 pm – 4:00 pm Location View location on My PrincetonU Related link More details in My PrincetonU Details Event Description This workshop will introduce participants to the Julia programming language. Julia is a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional statically-typed languages. One can write code in Julia that is nearly as fast as C. Julia features optional typing, multiple dispatch, and good performance, achieved using type inference and just-in-time (JIT) compilation, implemented using LLVM. It is multi-paradigm, combining features of imperative, functional, and object-oriented programming. Learning objectives: To learn about the Julia programming language and to write and run Julia code on the Research Computing clusters. Knowledge prerequisites: Some knowledge of computer programming Hardware/software prerequisites: (1) Bring a laptop which can connect to the eduroam wireless network. You will also need to be able to Duo authenticate to use campus resources. (2) Have an SSH client (https://bit.ly/3QER9Sv) installed on your laptop. (3) Register for an account on Adroit (https://bit.ly/3wicSaH) and make sure that you can SSH to Adroit before the workshop (https://bit.ly/3QER9Sv). Session format: Demonstration and hands-on Instructor bio: Colin joined the RSE group at Princeton in May 2021 in affiliation with the Initiative for Data-Driven Social Science. His work focuses on creating open-source statistical software and building systems to manage and facilitate research on large-scale social science databases. In his past research, he has developed methods to forecast high-frequency trade activity and predict mutual fund returns using machine learning methods. Prior to Princeton, Colin held roles as a quantitative researcher at Jacobs Levy Equity Management and as the lead data scientist at Nova Credit Inc.