Julia Solutions

Comprehensive guide to learning data science for a Julia programmer, right from the exploratory analytics part to the visualization part. 
A practical approach to learn the easy way Julia programming Follow 
Get an extensive coverage of Julia’s packages for statistical analysis 
This video-based approach will help you get familiar with the key concepts in Julia

Want to handle everything that Julia can throw at you and get the most out of it every day? This practical guide to programming with Julia for performing numerical computing will make you more productive and able to work with data more efficiently. The video starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We will also show you how to use the Julia language to identify, retrieve and transform data sets so that you can perform data analysis and data manipulation. Later, you’ll see how to optimize data science programs with parallel computing and memory allocation. You will get acquainted with the concepts of package development and networking to solve numerical problems using the Julia platform.

This video course includes recipes for 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.