Julia is a relatively new programming language, one meant for use with data analysis (aka “data science”). Julia aims to simultaneously provide a low threshold for entry (so that non-programmers can analyze their data without learning too much about programming) and high-performance execution. How does Julia manage to do this, and how do the results compare with a language such as Python‘s NumPy and SciPy? In this talk, Leah Hanson describes Julia’s aims, the differences between Julia and other languages (such as Python), and what how these design decisions have affected the resulting language.