Overview

This course on the Julia computer language aims to teach learners how to use Julia for simple medical statistical analysis. The course covers a wide range of topics including basic coding in Julia, working with different data types, control flow structures, functions, collections, strings, and packages like Gadfly for data visualization. The teaching method includes tutorials, practical examples, and a project to apply the learned concepts. This course is intended for individuals interested in learning a high-performance programming language for data analysis and scientific computing.

Syllabus

Julia for simple medical statistical analysis.
Using Distributions in Julia.
Lesson 01_01 Introducing Julia.
Lesson 01_02 Introducing the juliabox notebook.
Lesson 01_03 Something other than Hello World.
Lesson 01_04 How to code 1 plus 1 in Julia.
Lesson 01_05 A more functional way of coding 1 plus 1.
Lesson 01_06 Multiplication before addition.
Lesson 01_07 Rounding and common divisors and multiples.
Lesson 01_08 Trigonometric functions and sign values.
Lesson 01_09 Comparing values.
Lesson 01_10 Roots exponentials and logarithms.
Lesson 01_11 Complex numbers.
Lesson 01_12 Plotting with Gadfly.
Lesson 02_01 Introducing the concept of types.
Lesson 02_02 Super and subtypes.
Lesson 02_03 Abstract and concrete types.
Lesson 02_04 Creating your own types.
Lesson 03_01 Ternary operators.
Lesson 03_02 Boolean switching.
Lesson 03_03 For loops.
Lesson 03_04 If statements.
Lesson 03_05 Combining for loops and if statements using continue.
Lesson 03_06 Comprehensions.
Lesson 03_07 Collections.
Lesson 03_09 While statements.
Lesson 04_01 Introduction to Julia functions.
Lesson 04_02 Single expression functions.
Lesson 04_03 Multiple expression functions.
Lesson 04_04 Arguments with default values and keyword arguments.
Lesson 04_05 Functions with a variable number of arguments.
Lesson 04_06 Passing arrays as functions.
Lesson 04_07 Type parameters.
Lesson 04_08 Stabby functions and do blocks.
Lesson 04_09 Functions as arguments and nested functions.
Lesson 04_10 Multiple dispatch.
Lesson 05_01 Collections.
Lesson 05_02 Arrays.
Lecture 05_03 Modifying arrays.
Lesson 05_04 Matrices.
Lesson 05_05 Sets.
Lesson 05_06 Tuples.
Lesson 05_07 Dictionaries.
Lesson 06_01 Strings.
Lesson 06_02 Introduction to strings.
Lesson 06_03 Substrings.
Lesson 06_04 Characters.
Lesson 06_05 Splitting and combining strings.
Lesson 06_06 Converting between numbers and strings.
Lesson 06_07 Replacing sections of a string.
Lesson 06_08 Regular expressions.
Package Gadfly 01 Introduction to Julia Gadfly.
Package Gadfly 02 Layers Themes Titles Labels and Saving.
Package Gadfly 03 DataFrame Data and Boxplots.
Package Gadfly 04 Density plots Histograms and Violin plots for @JuliaLanguage.
Package Gadfly 05 QQ plots for @JuliaLanguage.
Package Gadfly 06 Scatter plots Lines More examples.
Project 1 Section 1 Part 1.
Project 1 Section 1 Part 2 The research question.
Project 1 Section 1 Part 3 Literature search.
Project 1 Section 1 Part 4 Study type.
Project 1 Section 1 Part 5 Variables required to answer research question.
Project 1 Section 1 Part 6 Stating the research hypotheses.
Project 1 Section 1 Part 7 Protocol and ethics.
Project 1 Section 1 Part 8 Data collection design.
Project 1 Section 1 Part 9 Google forms.
Project 1 Section 2 Part 1.
Project 1 Section 2 Part 2.
Project 1 Section 2 Part 3.
Project 1 Section 2 Part 4.
Project 1 Section 2 Part 5.
Project 1 Section 2 Part 6.
Project 1 Section 2 Part 7.