The Julia Programming Language Courses

Understanding the Discrete Fourier Transform - Week 14

Explore Discrete Fourier Transform using Julia, from basic concepts to implementation. Compare DFT with Fast Fourier Transform, analyze sounds, and understand computational complexity.

• YouTube
• 35 minutes
• On-Demand
• Free Video

Raytracing in 2D - Week 8 - MIT Fall 2020

Explore 2D raytracing, covering light behavior, reflection, refraction, and Snell's law. Learn to implement these concepts in code using Julia, with practical examples like mirrors and lenses.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Macroscopic Models of Epidemic Dynamics - Week 6

Explore macroscopic epidemic models, transitioning from stochastic to deterministic approaches. Learn about SIR models, continuous-time dynamics, and differential equations in epidemiology.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Data Wrangling Techniques in Julia - Part 2 - Tom Kwong

Explore advanced data wrangling techniques in Julia, covering reading, cleaning, tidying, analyzing, and visualizing data using two sample datasets for practical application.

• YouTube
• 48 minutes
• On-Demand
• Free Video

Data Wrangling Techniques in Julia - Part 1 - Tom Kwong

Comprehensive overview of data wrangling in Julia, covering ecosystem, workflow stages (read, clean, tidy, analyze, visualize), and DataFrames.jl resources for effective data science practices.

• YouTube
• 37 minutes
• On-Demand
• Free Video

Graphs, Trees, and Spreading Disease - MIT 18.S191 Fall 2020 Week 5

Explore graph theory, tree traversal, and epidemic modeling using Julia programming, with hands-on demonstrations and practical applications in network analysis and disease spread simulation.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Probability via Computation - Week 4

Explore probability concepts through computational methods, covering random sampling, Monte Carlo simulations, Bernoulli trials, and the Central Limit Theorem with practical examples and visualizations.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Understanding Structure in Data - Week 3

Explore data structure analysis using Julia, covering matrix rank, data visualization, PCA, and building a simple recommendation engine. Gain practical insights into advanced data science concepts.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Structure and Matrices in Julia Programming - Lecture 3

Explore matrices, sparse structures, and SVD for image compression and computational thinking in Julia, with practical applications in machine learning and linear algebra.

• YouTube
• 33 minutes
• On-Demand
• Free Video

Seam Carving: Live Coding Session - MIT 18.S191 Fall 2020 - Week 2

Live coding session demonstrating seam carving algorithm implementation in Julia, covering energy calculation, seam generation, and image manipulation techniques for content-aware image resizing.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Seam Carving and Dynamic Programming - Week 2 - MIT Fall 2020

Explore seam carving algorithm for intelligent image resizing, covering edge detection with gradients and optimal path finding using dynamic programming.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Convolutions in Image Processing - MIT 18.S191 Fall 2020 - Week 1

Explore image processing convolutions, from basic blurs to edge detection, using Julia. Learn about kernels, computational complexity, and connections to Fourier transforms.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Adventures in Computing - From Punch Cards to Differential Equations

Prof Linda Petzold explores her journey in computational science, from punch cards to modern differential equations, highlighting key developments in numerical methods, stochastic simulations, and their applications in various fields.

• YouTube
• 50 minutes
• On-Demand
• Free Video

State of Julia - JuliaCon 2020

Comprehensive overview of Julia's progress, highlighting key developments in multithreading, infrastructure, ecosystem, and future plans, with insights on challenges and upcoming features.

• YouTube
• 40 minutes
• On-Demand
• Free Video

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
• On-Demand
• Free Video