
Set up the Atom or Juno based Julia environment and begin the introduction to Julia programming.
Install Julia from the official site, set up with Jupyter notebooks or Julia prompt, and authenticate to download packages; this leads to organizing a project folder for the course.
Explore Julia's type system, static and dynamic typing, and primitive, composite, and parametric types. Understand integers and floats, hex literals, wraparound, big floats, infinity, NaN, and use convert and promote.
Explore Julia's arithmetic, bitwise, logical, and relational operators, learn unary and binary forms, and use the dot operator for element-wise array operations.
Explore how Julia's data structures organize fast, grouped data for efficient storage and use. Learn to leverage these structures to replace scattered variables.
Explore how dictionaries store key-value pairs in Julia, create dictionaries with pair constructors or assignments, and access, merge, and delete mappings while noting dictionaries are unordered.
Explore conditional evaluation in Julia using if else branches driven by boolean expressions. Understand variable scope within if blocks and the ternary operator for inline conditions.
Master variables, data storage, and control constructs like if conditions and loops in Julia. Learn to avoid duplicating code by writing your own functions and methods.
Explore Julia function arguments, including variable-length parameters with ellipsis, optional defaults, and keyword forms, then improve readability with do-blocks and functional mapping.
Explore variable scope in Julia, distinguishing local scope from global scope, and build on core structures, data storage, and control and code flow to write programs.
Explore how local scope confines variables to loops, functions, and blocks in Julia. See inner scopes hide variables from outer scopes, with global scope available but best used sparingly.
Data science, machine learning, Python, R are the buzzwords of the new decade! Do you aspire to become the next programming wizard and be a cut above the rest? The Julia programming language is the programming language of the future that is as easy to learn as python and as fast as C! Truly a best of both worlds!
About Julia
Julia was designed to have the following features:
· Open Source
· Easy to use, read, learn
· Computational performance like no other. Near C – like performance
· Abstraction and parallel programming capabilities.
Julia has
· Flexibility of dynamic untyped and interpreted languages like python and R
· Speed of statically typed and compiled languages like C or C++
Learn Julia Fundamentals
This Julia programming course will teach you the basics of Julia and the basics of computer programming You will be guided to install and setup your Julia environment using JuliaPro. You will learn the basics all the way from how to use the IDE, to variables, to functions all the way to writing your own computer programs in Julia from scratch!
Anyone who has a handle on typing on a computer will get through this course with flying colors. You don’t need any previous experience. This course is equally useful for those of you who are pros at programming and want to pick up a new language.
Data science, machine learning, Python, R are the buzzwords of the new decade! Do you aspire to become the next programming wizard and be a cut above the rest? The Julia programming language is the programming language of the future that is as easy to learn as python and as fast as C! Truly a best of both worlds!
Learn the next-generation of fast scientific computing with this Julia Fundamentals 2020 course and flaunt your talent to the computer science industry!
We cover the following in this course:
· Introduction and Installation of Julia
· Julia Programming Fundamentals
· Strings in Julia
· Data Structures in Julia
· Control flow mechanisms in Julia
· Variables and scope in the Julia programming language
· HANDS ON CODING in Julia!
What are you waiting for? Enroll Now!
About the Instructor
Ayush Hate is a professional software developer with experience in many different programming languages, often in combination. Ayush Hate has worked in C, C++, C#, Java, Python and R on large scale industry projects with experience in Machine Learning, Data Science and scalable application development. Teaching and giving back to the computer science community is his main aim as he continues to work to create courses for the future of programming!
Happy Programming!