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Mindmajix Julia Training briefs the basics of the Julia programming language with a strong focus on numerical accuracy, scientific computing and statistics. Julia programs are organized around the multiple dispatch; by defining functions and overloading them for different argument types, which can also be user-defined.
You will be exposed to the complete Julia Trainingcourse details in the below sections.
What niche is filled by Julia
How can Julia help you with data analysis
Getting started with Julia’s REPL
Alternative environments for Julia development: Juno, IJulia and Sublime-IJulia
The Julia ecosystem: documentation and package search
Getting more help: Julia forums and Julia community
Introduction to Julia REPL and batch execution via “Hello World”
Julia String Types
What is a variable? Why do we use a name and a type for it?
Integers
Floating point numbers
Complex numbers
Rational numbers
Vectors
Matrices
Multi-dimensional arrays
Heterogeneous arrays (cell arrays)
Comprehensions
Tuples
Ranges
Dictionaries
Symbols
Abstract types
Composite types
Parametric composite types
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 changing their input
Anonymous functions
Optional function arguments
Required function arguments
Inner constructors
Outer constructors
Compound expressions and scoping
Conditional evaluation
Loops
Exception Handling
Tasks
Modules
Packages
Symbols
Expressions
Quoting
Internal representation
Parsing
Evaluation
Interpolation
Filesystem
Data I/O
Lower Level Data I/O
Dataframes
Defining distributions
Interface for evaluating and sampling from distributions
Mean, variance and co variance
Hypothesis testing
Generalized linear models: a linear regression example
Plotting packages: Gadfly, Winston, Gaston, PyPlot, Plotly, Vega
Introduction to Gadfly
Interact and Gadfly
Introduction to Julia’s message passing implementation
Remote calling and fetching
Parallel map (pmap)
Parallel for
Scheduling via tasks
Distributed arrays
Most of the Julia Jobs in the industry expect the following add-on skills. Hence, we offer these skills-set as FREE Courses (Basics) to ease your learning process and help you stay ahead of the competition.
Our Julia Training course aims to deliver quality training that covers solid fundamental knowledge on core concepts with a practical approach. Such exposure to the current industry use-cases and scenarios will help learners scale up their skills and perform real-time projects with the best practices.
30 hrs of Self-Paced Videos
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30 hrs of Remote Classes in Zoom/Google meet
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Mar 29 - Apr 13
07:00 PM
Weekdays
Apr 01 - Apr 16
07:00 PM
Weekend
Apr 05 - Apr 20
09:00 AM
Weekdays
Apr 08 - Apr 23
09:00 AM
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I opted for the Grunt Training from MindMajix. The trainer and coordinators are very helpful and knowledgeable about the course content. I am very happy with the trainers and support team, and they assist me 24/7. I thank MindMajix for the best training.
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