Stat 244: Computing for Statistics and Data Science with Julia
UC Berkeley
Offerings
Overview
Programming and computation for applications in statistics, data science and related fields, focusing on the use of Julia, a modern language that offers interactivity with high performance based on just-in-time compilation. The course will also cover the use of co-processors, in particular GPUs, through Julia and Python packages such as Jax and PyTorch. Topics will include data types, functional programming, multiple argument dispatch, memory use, efficiency, parallelization, robustness and testing.
Logistics
Three hours of lecture per week for seven weeks.
Prerequisites
Statistics 243 or Statistics 215A or equivalent background of (1) extensive experience with a language such as Python or R, (2) basic familiarity with programming concepts such as functional programming, object-oriented programming, variable scope, memory use, and data structures, and (3) familiarity with the basics of parallel processing.