By: JuliaLanguage YouTube

Re-posted from: http://www.youtube.com/watch?v=JoRn4ryMclc&feature=youtube_gdata

Parallel and distributed computing (http://docs.julialang.org/en/release-0.1/manual/parallel-computing/) have been an integral part of Julia’s capabilities from an early stage. This session describes existing basic capabilities, which can be used as building blocks for higher level parallel libraries.

Lab: https://github.com/JuliaLang/julia-tutorial/raw/master/NumericalOptimization/tutorial.pdf
Solution: https://github.com/JuliaLang/julia-tutorial/blob/master/NumericalOptimization/Tutorial.jl

By: JuliaLanguage YouTube

Re-posted from: http://www.youtube.com/watch?v=XRClA5YLiIc&feature=youtube_gdata

DataFrames (https://github.com/HarlanH/DataFrames.jl) is one of the most widely used Julia packages. This session is an introduction to data analysis with Julia using DataFrames.

Slides: https://github.com/JuliaLang/julia-tutorial/raw/master/DataFrames/slides.pdf

By: JuliaLanguage YouTube

Re-posted from: http://www.youtube.com/watch?v=OFWYPqwVtHU&feature=youtube_gdata

The Grid of Resistors is a classic numerical problem to compute the voltages and the effective resistance of a 2n+1 by 2n+2 grid of 1 ohm resistors if a battery is connected to the two center points. As part of this lab, the problem is solved in Julia in a number of different ways such as a vectorized implementation, a devectorized implementation, and using comprehensions, in order to study the performance characteristics of various methods.

Lab: https://github.com/JuliaLang/julia-tutorial/blob/master/GridOfResistors/GridOfResistors.md
Solution: https://github.com/JuliaLang/julia-tutorial/tree/master/GridOfResistors