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Course Outline
Introduction to Julia
- Identifying the unique niche Julia occupies
- Leveraging Julia for data analysis tasks
- Key learning outcomes from this course
- Getting started with Julia's REPL
- Exploring alternative development environments: Juno, IJulia, and Sublime-IJulia
- Navigating the Julia ecosystem: documentation and package discovery
- Seeking additional support through Julia forums and the community
Strings: Hello World
- Introduction to Julia REPL and batch execution via a "Hello World" example
- Understanding Julia String Types
Scalar Types
- Understanding variables: the importance of names and types
- Integers
- Floating point numbers
- Complex numbers
- Rational numbers
Arrays
- Vectors
- Matrices
- Multi-dimensional arrays
- Heterogeneous arrays (cell arrays)
- Using 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
- Understanding 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 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 operations
- Data I/O
- Low-level Data I/O
- DataFrames
Distributions and Statistics
- Defining statistical distributions
- Interface for evaluating and sampling from distributions
- Calculating mean, variance, and covariance
- Hypothesis testing
- Generalized linear models: a linear regression example
Plotting
- Overview of plotting packages: Gadfly, Winston, Gaston, PyPlot, Plotly, and Vega
- Introduction to Gadfly
- Integrating Interact with Gadfly
Parallel Computing
- Introduction to Julia's message passing implementation
- Remote calling and fetching
- Parallel map (pmap)
- Parallel for loops
- Scheduling via tasks
- Distributed arrays
Requirements
While a basic understanding of programming concepts is beneficial, it is not a strict requirement. The course is designed to provide a comprehensive, self-contained introduction to the fundamentals of the Julia programming language.
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
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