This chapter gets you started with Julia for machine learning. We first look at why Julia is well-suited for ML tasks, particularly its performance benefits and features for scientific computing. You will then proceed to set up your Julia development environment, installing the language itself and key packages. Following that, we will examine Julia's type system and the concept of multiple dispatch, along with essential syntax for data manipulation. The chapter will also guide you through working with arrays, matrices, and the DataFrames.jl package for handling tabular data. Finally, you will learn to use Pkg.jl, Julia's built-in package manager, for managing project dependencies.