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Programming with Julia

  • Development
  • Jan 07, 2025
SynopsisProgramming with Julia, available at $84.99, has an average r...
Programming with Julia  No.1

Programming with Julia, available at $84.99, has an average rating of 4.22, with 72 lectures, 35 quizzes, based on 475 reviews, and has 4642 subscribers.

You will learn about Learn the groundbreaking Julia language: Speed of C, ease of Python Master Julia language to be able to use it in data science, machine learning and artificial intelligence Learn the fundamental principles of programming that you can use while learning other programming languages. Program in Julia language professionally This course is ideal for individuals who are This course is for anyone who wants to learn Julia programming language. You dont need any prior programming knowledge. or If you want to learn data science, machine learning, deep learning and artificial intelligence, and search for an ideal programming language Julia is the best fit for you. It is particularly useful for This course is for anyone who wants to learn Julia programming language. You dont need any prior programming knowledge. or If you want to learn data science, machine learning, deep learning and artificial intelligence, and search for an ideal programming language Julia is the best fit for you.

Enroll now: Programming with Julia

Summary

Title: Programming with Julia

Price: $84.99

Average Rating: 4.22

Number of Lectures: 72

Number of Quizzes: 35

Number of Published Lectures: 72

Number of Published Quizzes: 35

Number of Curriculum Items: 107

Number of Published Curriculum Objects: 107

Original Price: $27.99

Quality Status: approved

Status: Live

What You Will Learn

  • Learn the groundbreaking Julia language: Speed of C, ease of Python
  • Master Julia language to be able to use it in data science, machine learning and artificial intelligence
  • Learn the fundamental principles of programming that you can use while learning other programming languages.
  • Program in Julia language professionally
  • Who Should Attend

  • This course is for anyone who wants to learn Julia programming language. You dont need any prior programming knowledge.
  • If you want to learn data science, machine learning, deep learning and artificial intelligence, and search for an ideal programming language Julia is the best fit for you.
  • Target Audiences

  • This course is for anyone who wants to learn Julia programming language. You dont need any prior programming knowledge.
  • If you want to learn data science, machine learning, deep learning and artificial intelligence, and search for an ideal programming language Julia is the best fit for you.
  • Do you want to learn data science, machine learning, deep learning, and AI but you are not sure about the programming language to learn?

    Or you may be using Python and R, but you are tired of their low speed.

    Julia is a modern programming language developed for data science, machine learning and AI. It is a dynamically typed language which is easy to learn and use and has the speed of C.

    This is the first of a series of courses I plan to teach data science, machine learning and deep learning using Julia. Other courses, “Data Science with Julia”, “Machine Learning with Julia” and “Deep Learning with Julia” will follow. In this course, you will learn programming in Julia proficiently. In the upcoming courses you will learn both machine learning and deep learning algorithms and how to build those algorithms from scratch using Julia.

    Besides being ideal for data science and machine learning, Julia is also ideal for production environments. Being one of the most modern languages, Julia can be used to build entire applications and microservices.

    Julia combines best features of dynamic languages like Python and R and low-level languages like C, C# and Java. You can develop a machine learning model or an algorithm in Julia and use that code in a production environment. You don’t have to use different languages for development and production.

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Why Julia?

    Lecture 2: History of Julia

    Lecture 3: Codes and resources

    Chapter 2: Starting with Julia

    Lecture 1: Installing Julia

    Lecture 2: Installing Julia in Windows (Optional)

    Lecture 3: Installing Julia in Linux (Optional)

    Lecture 4: Julia REPL

    Lecture 5: Julia Editor and IDEs

    Chapter 3: Variables, Data Types and Operations

    Lecture 1: Introduction

    Lecture 2: Variables

    Lecture 3: Type Hierarchy in Julia

    Lecture 4: Numerical Data Types: Integers and Floating-Point Numbers

    Lecture 5: Numerical Data Types: Complex and Rational Numbers

    Lecture 6: Character and String Types

    Lecture 7: Primitive and Composite Types

    Lecture 8: Parametric Types

    Lecture 9: Basic Operations

    Lecture 10: Exercises: Variables, Data Types & Operations

    Lecture 11: Solutions to Exercises: Variables, Data Types & Operations

    Chapter 4: Data Structures

    Lecture 1: Introduction

    Lecture 2: Tuples

    Lecture 3: Dictionaries

    Lecture 4: Ranges

    Lecture 5: Arrays

    Lecture 6: Vectors and Matrices

    Lecture 7: Multidimensional Arrays

    Lecture 8: Broadcasting and Dot Syntax

    Lecture 9: Sets

    Lecture 10: Basic Linear Algebra

    Lecture 11: Exercises: Data Structures

    Lecture 12: Solutions to Exercises: Data Structures

    Chapter 5: Conditionals and Loops

    Lecture 1: Introduction

    Lecture 2: Compound Expressions

    Lecture 3: Conditional Evaluation

    Lecture 4: Short Circuit Evaluation

    Lecture 5: For Loops

    Lecture 6: While Loops

    Lecture 7: Continue and Break

    Lecture 8: Comprehensions

    Lecture 9: Exercises

    Lecture 10: Solutions

    Chapter 6: Functions

    Lecture 1: Introduction

    Lecture 2: Defining Functions

    Lecture 3: Map, Reduce, Filter

    Lecture 4: Variable Number of Arguments

    Lecture 5: Optional Arguments

    Lecture 6: Keyword Arguments

    Lecture 7: Composite Functions

    Lecture 8: Mutating Functions

    Lecture 9: Exercises

    Lecture 10: Solutions

    Chapter 7: Methods

    Lecture 1: Introduction

    Lecture 2: Multiple Dispatch

    Lecture 3: Parametric Methods

    Lecture 4: Function Like Objects

    Lecture 5: Constructors

    Lecture 6: Neural Networks Demo

    Chapter 8: Modules and Packages

    Instructors

  • Programming with Julia  No.2
    Dr. ?lker Arslan
    Data Science and Analytics Professional
  • Rating Distribution

  • 1 stars: 0 votes
  • 2 stars: 6 votes
  • 3 stars: 33 votes
  • 4 stars: 149 votes
  • 5 stars: 287 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

    Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!