Open Source/Julia Programming


Julia Programming Certification Training Course Overview

Julia is a programming language developed by researchers of MIT. It has been designed by keeping in mind the future of computing like: high-performance computing, parallel computing and machine learning. Usually with the help of programming a programmer tells the computer what to do, but now a days programming is not only about telling the computer what to do. There are some new areas of science which have recently emerged up, like machine learning, big data and AI. Special kind of programming is required in these fields and Julia is one such programming language. Julia is a perfect platform for the above technologies because it is one of the fastest language as well as fastest growing language today. Fields like machine learning and AI depends a lot on the performance and Julia fits much better in this because Julia code can run as fast as C code and sometimes even faster. In the past few years we have seen an exponential growth in the field of scientific computing which was done by some other good languages, but they may not have been the optimal languages for the task. Julia by contrast has been developed by keeping in mind the performance as prime factor for the above technologies. Some of the features of Julia are just in time compilation, interoperability with python C fortron, open source and cross platform.

 


Julia Programming (32 Hours) Download Course Contents

Live Virtual Classroom (Instructor-Led)

Fee : 1,400 (Includes Taxes) 
9 AM - 5 PM (Flexible Time Slots for 4 hours option)




April
8 Hours/Day
4 Hours/Day
19-22
19-28
May
8 Hours/Day
4 Hours/Day
03-06
09-12
10-13
17-20
03-12
09-18
10-19
17-26
June
8 Hours/Day
4 Hours/Day
07-10
13-16
14-17
21-24
07-16
13-22
14-23
21-30
July
8 Hours/Day
4 Hours/Day
05-08
11-14
12-15
05-14
11-20
12-21

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Course Prerequisites

  • Basic Understadning of Mathamatics and Programming .


A High Performance Language for Artificial Intelligecne and Machine learning.

  • It's easy to learn as the syntax is easy.
  • Good for scientific computing.
  • Good for multi-processing.
  • No special glue required to connect with other languages like C, fortron n python.

 

FAQ's

No, the published fee includes all applicable taxes.