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Julia programming

Programmation Julia

Yaé Ulrich Gaba

Undergraduate30 hours10 chaptersEN

Description

A hands-on course on the Julia programming language, from basics to advanced scientific computing and machine learning. Covers types, multiple dispatch, arrays, DataFrames, visualization (Plots.jl, Makie.jl), performance optimization, differential equations (DifferentialEquations.jl), and ML (MLJ.jl, Flux.jl). Uses Pluto notebooks and real datasets.

Table of contents

  1. Chapter 1 Getting started with Julia
  2. Chapter 2 Types, variables, and control flow
  3. Chapter 3 Functions and multiple dispatch
  4. Chapter 4 Arrays and linear algebra
  5. Chapter 5 DataFrames and data wrangling
  6. Chapter 6 Visualization
  7. Chapter 7 Performance
  8. Chapter 8 Scientific computing
  9. Chapter 9 Machine learning with Julia
  10. Chapter 10 Capstone projects

Prerequisites

Basic programming experience in any language. No prior Julia knowledge required.

Download

PDF ENCode & notebooks