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Course Outline
Getting Started with Julia
- Identifying the niche Julia fills
- Leveraging Julia for data analysis e>
- Course expectations and outcomes
- Introduction to Julia's REPL
- Alternative development environments: Juno, IJulia, and Sublime-IJulia
- Navigating the Julia ecosystem: documentation and package search
- Seeking further support: Julia forums and community resources
Strings: Hello World
- Introduction to Julia REPL and batch execution using 'Hello World'
- Understanding Julia String Types
Scalar Types
- Understanding variables: names and types
- Integers
- Floating-point numbers
- Complex numbers
- Rational numbers
Arrays
- Vectors
- Matrices
- Multi-dimensional arrays
- Heterogeneous arrays (cell arrays)
- List comprehensions
Other Elementary Types
- Tuples
- Ranges
- Dictionaries
- Symbols
Creating Custom Types
- Abstract types
- Composite types
- Parametric composite types
Functions
- Defining functions in Julia
- Julia functions as type-specific methods
- Multiple dispatch
- Differences between multiple dispatch and traditional object-oriented programming
- Parametric functions
- Functions with side effects (modifying inputs)
- Anonymous functions
- Optional function arguments
- Required function arguments
Constructors
- Inner constructors
- Outer constructors
Control Flow
- Compound expressions and scoping rules
- Conditional evaluation
- Loops
- Exception handling
- Tasks
Code Organization
- Modules
- Packages
Metaprogramming
- Symbols
- Expressions
- Quoting
- Internal representation
- Parsing
- Evaluation
- Interpolation
Reading and Writing Data
- Filesystem interactions
- Data input and output
- Low-level data I/O
- DataFrames
Distributions and Statistics
- Defining probability distributions
- Interface for evaluating and sampling 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
- Integration with Interact and Gadfly
Parallel Computing
- Overview of Julia's message-passing implementation
- Remote calling and fetching
- Parallel map (pmap)
- Parallel for loops
- Scheduling via tasks
- Distributed arrays
Requirements
While some prior programming experience is beneficial, it is not a strict requirement. The course aims to teach the fundamentals of the Julia programming language in a comprehensive, self-contained manner.
14 Hours