Statistics 244: Computing for Statistics and Data Science with Julia

UC Berkeley, Spring 2025

Course description

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.

Course materials

See the links above for the key resources for the course.

Most course content (in particular notes and problem sets) are available through this website via the links in the left sidebar.

Questions about taking the class

If you would like to audit the class, enroll as a UC Berkeley undergraduate, or enroll as a concurrent enrollment student (i.e., for visiting students), or for some other reason are not enrolled, please fill out this survey as soon as possible and, ideally, chat with me before/after the first class. All those enrolled or wishing to take the class should have filled it out by Wednesday January 24 at noon.

Please see the syllabus for the computing background I expect.