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Data Science. Introduction to Julia

This course is adaptive: it will adjust according to your skill

About the course

Hello!

Welcome to our course dedicated to the Julia programming language!

We believe that there are many good reasons to study Julia, especially for data scientists. The Julia programming language is a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional statically-typed languages.
Nowadays the popularity of Julia is rapidly increasing in the field of data science, high-performance computing and scientific computing.

Julia is a very young programming language. The work on the Julia project began at the Massachusetts Institute of Technology (MIT) in 2009. It became open source (MIT licensed) in 2012.
Anyone competent in MATLAB can easily learn Julia because it's syntax is very similar to MATLAB. But it is not a MATLAB clone. Some advantages of Julia over comparable systems include:

  1. User-defined types are as fast and compact as built-ins
  2. No need to vectorize code for performance
  3. Designed for parallelism
  4. Powerful type system
  5. Elegant and extensible conversions and promotions for numeric and other types
  6. Efficient support for Unicode
  7. Call C functions directly (no wrappers or special APIs needed)
  8. Powerful shell-like capabilities for managing other processes

Instructors

  1. User picture
    Evgeniya Vorontsova
    Associate Professor, PhD, Far Eastern Federal University.
    Topics: Mathematical Programming, Machine Learning, Python, C++ Programming, Graph Theory, Education https://www.researchgate.net/profile/Evgeniya_Vorontsova/

Reviews

Rated:  5
Непонятно, почему курс по новому языку команда Stepik сделала адаптивным, ещё и вперемешку с Питоном и R (в рамках большого курса Data Science). По-моему, это только отпугнёт потенциальных пользователей языка (ничего не понятно, а уже просят какие-то задачи решать). Для нормального введения советую проследовать на youtube по запросу julia language. Очень интересная альтернатива python, особенно если скорости numpy уже не хватает для задач/не векторизуется/замучились с cython-ом.
5 All reviews

This practical course will help you to begin studying Julia, a modern dynamic programming language, appropriate for scientific and numerical computing.

Expected time to complete:
1 hour
Language:
English
Certificate:
Not issuing
Certificate:
Not issuing

About the course

Hello!

Welcome to our course dedicated to the Julia programming language!

We believe that there are many good reasons to study Julia, especially for data scientists. The Julia programming language is a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional statically-typed languages.
Nowadays the popularity of Julia is rapidly increasing in the field of data science, high-performance computing and scientific computing.

Julia is a very young programming language. The work on the Julia project began at the Massachusetts Institute of Technology (MIT) in 2009. It became open source (MIT licensed) in 2012.
Anyone competent in MATLAB can easily learn Julia because it's syntax is very similar to MATLAB. But it is not a MATLAB clone. Some advantages of Julia over comparable systems include:

  1. User-defined types are as fast and compact as built-ins
  2. No need to vectorize code for performance
  3. Designed for parallelism
  4. Powerful type system
  5. Elegant and extensible conversions and promotions for numeric and other types
  6. Efficient support for Unicode
  7. Call C functions directly (no wrappers or special APIs needed)
  8. Powerful shell-like capabilities for managing other processes

This course is entirely free. All content is available now.