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Course Outline
Introduction to Julia
- Understanding the niche Julia fills
- How Julia can assist with data analysis
- Key takeaways from this course
- Getting started with Julia's REPL
- Alternative Julia development environments: Juno, IJulia, and Sublime-IJulia
- Navigating the Julia ecosystem: documentation and package search
- Accessing further assistance: Julia forums and community
Strings: Hello World
- Introduction to the Julia REPL and batch execution via "Hello World"
- Julia String Types
Scalar Types
- Understanding variables: the purpose of 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
- Defining functions in Julia
- Julia functions as methods operating on types
- Multiple dispatch
- Differences between multiple dispatch and traditional object-oriented programming
- Parametric functions
- Functions that modify their inputs
- 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 operations
- Data I/O
- Low-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 prior familiarity with programming is advantageous, it is not strictly required. The course aims to teach the fundamentals of the Julia programming language in a comprehensive and self-contained manner.
14 Hours
