The Julia Programming Language Courses

Scientific Machine Learning: Opportunities and Challenges - Keynote

Explore Scientific Machine Learning: combining physics-based models with ML for complex phenomena, addressing challenges in computational science, and revolutionizing fields like rocket engine combustion analysis.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

DFTK - A Julian Approach for Simulating Electrons in Solids

Introducing DFTK: A Julia package for density-functional theory simulations, offering flexibility for practical calculations and mathematical development in electronic structure research.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Loop Analysis and Vectorization in Julia - JuliaCon 2020

Explore LoopVectorization.jl for efficient loop representation, cost modeling, and vectorization strategies in Julia, enhancing performance through intra-core parallelism and SIMD operations.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

BinaryBuilder.jl - The Subtle Art of Binaries That Just Work

Explore BinaryBuilder.jl for compiling binary libraries across Julia platforms. Learn to create build recipes, use the wizard, and contribute to Yggdrasil. Hands-on experience included.

• YouTube
• 2 hours 25 minutes
• Self-Paced
• Free Video

Developing Julia Packages

Comprehensive guide to creating, testing, and contributing Julia packages. Covers development environments, continuous integration, version control, and open-source collaboration.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

Interval Methods for Scientific Computing in Julia

Explore interval methods for scientific computing in Julia, focusing on constraint propagation, global optimization, and root finding using IntervalConstraintProgramming.jl and IntervalArithmetic.jl packages.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

What's Bad About Julia - Addressing Fundamental Issues

Julia co-creator Jeff Bezanson discusses fundamental issues in the language, focusing on modularity, types, and method specificity rules, offering insights into potential solutions for a better programming experience.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Multi-threading in Julia with PARTR - JuliaCon 2019

Explore multi-threading in Julia with PARTR, covering old and new features, future developments, and practical examples. Includes performance comparisons and Q&A on threading models and implementation details.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

An Introduction to Julia for Beginners

Comprehensive introduction to Julia programming, covering basics to advanced topics. Ideal for beginners with technical computing needs and experience in other languages.

• YouTube
• 1 hour 58 minutes
• Self-Paced
• Free Video

Flux - The Elegant Machine Learning Library for Julia

Explore Flux, an intuitive machine learning library for Julia, featuring state-of-the-art performance, automatic differentiation, and innovative compiler technology for efficient and flexible ML development.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Tricks and Tips in Numerical Computing - Keynote

Explore advanced numerical computing techniques, from complex differentiation to low-precision arithmetic, with insights on error analysis, matrix operations, and IEEE standards for improved computational accuracy and efficiency.

• YouTube
• 56 minutes
• Self-Paced
• Free Video

Shared Memory Parallelism in Julia with Multi-Threading - Parallel Depth-First Scheduling

Explore efficient shared memory parallelism in Julia using multi-threading, focusing on nested parallelism and the parallel depth-first scheduling approach for improved performance.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Celeste.jl - Petascale Computing in Julia

Explore Celeste.jl, a Julia-based project for petascale astronomical image analysis using Bayesian inference, showcasing Julia's power in high-performance computing and data science on supercomputers.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

A Superfacility Model for Data-Intensive Science

Explore data-intensive science challenges, high-performance computing, and the role of programming languages like Julia in addressing big data and computational demands in scientific research.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Ray.jl - Julia Runtime and Client for the Ray Compute Framework

Explore Ray.jl, a Julia client for the Ray compute framework. Learn about distributed computing, implementation challenges, and real-world applications in scaling workloads.

• YouTube
• 28 minutes
• Self-Paced
• Free Video