Julia Programming for Machine Learning

Welcome to this online course on Julia! This course is for anyone who wants to learn Julia programming for problem solving. Machine learning and data science are the well applied domains of Julia programming. Above all, Julia is a fast and highly efficient programming language for scientific computation. Master Julia syntax for coding through arranged topics and exercises in this course.

Full–fledged segment in this course is dedicated to know about core concept of data manipulation in Julia which is an essential part of data analysis.

This course includes 4 projects on “data analysis” and for building “machine learning models based on regression analysis”, to learn the usage of Julia packages for data analysis and machine learning.

With data manipulation and building machine learning models, we will see the usage of Julia package StatsPlots for data visualization.

By the end of this course, you will know how to work with Julia syntax for

writing Julia program.

working with several datatypes and data–structures.

creating and manipulating arrays.

working with raw text.

defining functions and macros.

metaprogramming.

creating objects from new datatype that can be defined in Julia.

data manipulation in DataFrame and TimeArray objects.

building machine learning models for numeric prediction.