Julia
High-performance language for numerical computing.
Julia is taught here in 3 lessons, running from Syntax and the type system through to Packages, environments and performance. Each lesson takes one topic, shows the working code, and links onward to the next, so the course can be read straight through in order.
| Track | Python & Data Science |
| Lessons | 3 |
| Level | Beginner |
| Reading time | about 39 minutes |
| Prerequisites | Helpful, but not required: R |
Lessons
- Syntax and the type systemFunctions, arrays and interpolation, plus the concrete and abstract types that decide how fast the code runs.
- Multiple dispatchMethods are selected on the types of all their arguments, which replaces type tags, if/else chains and class hierarchies.
- Packages, environments and performanceReproducible project environments with Pkg, and the handful of rules that separate fast Julia from slow Julia.
More in Python & Data Science
Python 3 NumPy pandas Matplotlib Jupyter Notebook Flask FastAPI Django SciPy Pillow Python 2.x R
FAQ
How long does the Julia course take?
It has 3 lessons, about 39 minutes of reading. Expect roughly twice that if you type out and run every example.
Do I need prior experience for Julia?
Not strictly. It helps to have read R first, because some lessons build on it, but every lesson explains its own assumptions.
What should I read after Julia?
This is the last course in Python & Data Science right now. Browse the other tracks from the courses index to go sideways.
Last refreshed 2026-09-18.