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Julia for Data Science

High-performance scientific computing. Solve the 'two-language problem' by writing code as fast as C with the syntax of Python.

Julia is designed for speed. It solves the issue where developers prototype in Python but rewrite in C++ for performance. This course teaches you the Julia language features: Just-In-Time (JIT) compilation, Multiple Dispatch, and its powerful type system. You will learn to write high-performance code for scientific simulations, differential equations, and machine learning. Perfect for data scientists hitting the performance limits of Python.

✅ 100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
SciComp
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Complete Course Syllabus

  • 1
    Julia Basics
    Syntax, REPL, and the Just-In-Time compiler.
  • 2
    Type System
    Understanding types and Multiple Dispatch paradigm.
  • 3
    Performance optimization
    Writing type-stable code and avoiding allocations.
  • 4
    Data Science Stack
    DataFrames.jl and plotting with Makie.
  • 5
    Differential Equations
    Solving ODEs using the world-class DifferentialEquations.jl.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$120k - $160k

Career Paths

Quantitative Developer $130k-$180k
Scientific Researcher $110k-$150k
HPC Engineer $120k-$160k

What You Will Learn

Write high-performance scientific code that rivals C/C++
Leverage Multiple Dispatch for extensible and clean architecture
Solve complex differential equations efficiently
Interface with Python and R libraries directly from Julia
Build machine learning models using the Flux.jl library

Skills You Will Gain

Julia Scientific Computing High-Performance Computing Multiple Dispatch Flux.jl

Who Is This For

Quant Researchers
Scientific Modelers
HPC Engineers

Prerequisites

Python/R experience
Math background

Julia for Data Science FAQs

Faster than Python?

Yes, significantly faster for numerical loops.

Why not just C++?

Julia is as easy to read/write as Python.

Job market?

Niche but growing in Finance and Science.

Libraries?

Growing ecosystem, plus can call Python libraries.

Need more info?
All Reork courses are 100% free, self-paced, and fully accessible on mobile devices. No prior experience is required. Read our full Platform FAQ.

Tech Stack & Tools

Julia
Pluto.jl
VS Code
Jupyter
Flux

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