Course Description

Are you looking forward to get well versed with Julia? Then this is the perfect course for you!

Julia is a young language with limited documentation and although rapidly growing, a small user community. Most developers today will know the object oriented paradigm used in mainstream languages such as Python, Java and C++. This presents a challenge switching to Julia which is more functionally oriented.

With this comprehensive 2-in-1 course takes a practical and incremental approach.  It teaches the fundamentals of Julia to developers with basic knowledge of programming. It is taught in a hands on approach, with simple programming examples the student can try themselves. Building on that, it will invite the user to a tour of the ecosystem of Julia through practical code examples.

By end of this course you will more productive and acquire all the skills to work with data more efficiently. Also help you quickly refresh your knowledge of functions, modules, and arrays & shows you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation & also get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Getting Started With Julia covers complete INSTALLATION AND SETUP along with basic of Julia. This course will not only introduce the language, but also explain how to think differently about problems with the Julia approach.  This course also focuses various aspects such as Functional Programming in Julia, Metaprogramming, Debugging and Testing & much more.

The second course, Julia Solutions covers consist complete guide to programming with Julia for performing numerical computation will make you more productive and able to work with data more efficiently. The course starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We’ll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, you’ll see how to optimize data science programs with parallel computing and memory allocation. You’ll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.

This course also includes videos on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the course, you will acquire the skills to work more effectively with your data.

About the Authors:

  • Erik Engheim* is a professional mobile developer with experience in many different programming languages, often in combination. Erik Engheim has worked with C/C#, Java, C++, Objective-C, and Swift before moving into Julia. His experience with Julia involves automation, and high performance processing of code strings.

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in machine learning, data science, data analysis, computational statistics, and natural language processing (NLP). Rohit currently works as a senior data scientist at Zomato, also having worked as the first data scientist at Kayako.He is part of the Julia project, where he develops data science models and contributes to the codebase. Additionally, Raj is also a Mozilla contributor and volunteer, and he has interned at Scimergent Analytics.

Course Details
en
en
Packt Publishing
Self-paced
Beginner
13 hours
Course Details
en
en
Packt Publishing
Self-paced
Beginner
13 hours
Course Description

Are you looking forward to get well versed with Julia? Then this is the perfect course for you!

Julia is a young language with limited documentation and although rapidly growing, a small user community. Most developers today will know the object oriented paradigm used in mainstream languages such as Python, Java and C++. This presents a challenge switching to Julia which is more functionally oriented.

With this comprehensive 2-in-1 course takes a practical and incremental approach.  It teaches the fundamentals of Julia to developers with basic knowledge of programming. It is taught in a hands on approach, with simple programming examples the student can try themselves. Building on that, it will invite the user to a tour of the ecosystem of Julia through practical code examples.

By end of this course you will more productive and acquire all the skills to work with data more efficiently. Also help you quickly refresh your knowledge of functions, modules, and arrays & shows you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation & also get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Getting Started With Julia covers complete INSTALLATION AND SETUP along with basic of Julia. This course will not only introduce the language, but also explain how to think differently about problems with the Julia approach.  This course also focuses various aspects such as Functional Programming in Julia, Metaprogramming, Debugging and Testing & much more.

The second course, Julia Solutions covers consist complete guide to programming with Julia for performing numerical computation will make you more productive and able to work with data more efficiently. The course starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We’ll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation. Later on, you’ll see how to optimize data science programs with parallel computing and memory allocation. You’ll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.

This course also includes videos on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the course, you will acquire the skills to work more effectively with your data.

About the Authors:

  • Erik Engheim* is a professional mobile developer with experience in many different programming languages, often in combination. Erik Engheim has worked with C/C#, Java, C++, Objective-C, and Swift before moving into Julia. His experience with Julia involves automation, and high performance processing of code strings.

Jalem Raj Rohit is an IIT Jodhpur graduate with a keen interest in machine learning, data science, data analysis, computational statistics, and natural language processing (NLP). Rohit currently works as a senior data scientist at Zomato, also having worked as the first data scientist at Kayako.He is part of the Julia project, where he develops data science models and contributes to the codebase. Additionally, Raj is also a Mozilla contributor and volunteer, and he has interned at Scimergent Analytics.