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Course Outline

Introduction to Julia

  • Identifying the niche Julia fills
  • How Julia can assist with data analysis
  • Expectations from this course
  • Getting started with Julia's REPL
  • Alternative development environments for Julia: Juno, IJulia, and Sublime-IJulia
  • The Julia ecosystem: documentation and package search
  • Additional resources: Julia forums and community

Strings: Hello World

  • Introduction to Julia REPL and batch execution via "Hello World"
  • Julia String Types

Scalar Types

  • Understanding variables: why we use names and types
  • Integers
  • Floating-point numbers
  • Complex numbers
  • Rational numbers

Arrays

  • Vectors
  • Matrices
  • Multi-dimensional arrays
  • Heterogeneous arrays (cell arrays)
  • Comprehensions

Other Elementary Types

  • Tuples
  • Ranges
  • Dictionaries
  • Symbols

Building Your Own Types

  • Abstract types
  • Composite types
  • Parametric composite types

Functions

  • How to define a function in Julia
  • Julia functions as methods operating on types
  • Multiple dispatch
  • How multiple dispatch differs from traditional object-oriented programming
  • Parametric functions
  • Functions that modify their input
  • Anonymous functions
  • Optional function arguments
  • Required function arguments

Constructors

  • Inner constructors
  • Outer constructors

Control Flow

  • Compound expressions and scoping
  • Conditional evaluation
  • Loops
  • Exception handling
  • Tasks

Code Organization

  • Modules
  • Packages

Metaprogramming

  • Symbols
  • Expressions
  • Quoting
  • Internal representation
  • Parsing
  • Evaluation
  • Interpolation

Reading and Writing Data

  • Filesystem
  • Data I/O
  • Lower-level Data I/O
  • Dataframes

Distributions and Statistics

  • Defining distributions
  • Interface for evaluating and sampling from distributions
  • Mean, variance, and covariance
  • Hypothesis testing
  • Generalized linear models: a linear regression example

Plotting

  • Plotting packages: Gadfly, Winston, Gaston, PyPlot, Plotly, Vega
  • Introduction to Gadfly
  • Interact and Gadfly

Parallel Computing

  • Introduction to Julia's message passing implementation
  • Remote calling and fetching
  • Parallel map (pmap)
  • Parallel for
  • Scheduling via tasks
  • Distributed arrays

Requirements

While some familiarity with programming is beneficial, it is not required. The course aims to teach the fundamentals of the Julia programming language in a self-contained manner.

 14 Hours

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