Learn the Julia programming language through hands-on tutorials covering databases, statistics, data manipulation, and linear algebra. Explore JuliaDB for selections, reductions, grouping, and joining tables. Import CSV files, perform gradient descent, and utilize Julia's Statistics Package. Dive into medical statistics, create plots with VegaLite, and set up Julia environments. Master complex numbers, Euclidean vector spaces, matrices, and linear systems using elementary row operations. Implement ordinary least squares, QR decomposition, bootstrap resampling, and hypothesis testing. Set up a development environment with Jupyter, Pluto notebooks, and VS Code to enhance your Julia programming skills.
Overview
Syllabus
Julia Language Database JuliaDB.
Selections in JuliaDB.
Reductions in JuliaDB.
Grouping in JuliaDB to calculate descriptive statistics.
Joining two tables in JuliaDB.
Importing a csv file in JuliaDB.
Gradient descent tutorial using Julia code.
Julia Statistics Package.
Julia Statistics Package.
Julia for medical statistics 2020 edition.
Julia plots using VegaLite.
Julia environments.
How to use Pluto notebooks and set Julia environments.
Complex numbers introduction using Julia.
Introduction to Euclidean vector spaces with Julia.
Tutorial on matrices with help from Julia.
Solving linear systems using elementary row operations with Julia.
Ordinary least squares tutorial using Julia.
Gram Schmidt process for QR decomposition using Julia.
Bootstrap resampling for confidence intervals and sampling distrubutions.
Estimating a p value for the difference in means between two groups.
F ratio sampling distribution under the null hypothesis using Julia.
Install Julia with Jupyter and Pluto notebooks and VS Code.
Taught by
Dr Juan Klopper
