Best programming language for data analysis, data science and machine learning
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What you'll learn
- Having a strong grasp of data frames in Julia
- Importing data with Julia
- Analyzing and manipulating data with Julia
- Data visualization with Julia
Description
Do you want to learn data analysis, data science, machine learning, deep learning, and AI, but you are not sure about the programming language to choose? Or perhaps you are using Python and R, but you are tired of their slow performance.
You can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them.
Julia is a modern programming language developed for data science, machine learning, AI, and numerical computing. It is a dynamically typed language that is easy to learn and use and moreover has the speed of C.
Julia combines the best features of dynamic languages like Python and R with low-level languages like C, C#, and Java. You can develop a machine learning model or an algorithm in Julia and use that code in a production environment. You don't have to use different languages for development and production.
This is my second course about Julia. In this course, you will learn how to accomplish essential data science tasks with Julia: importing, analyzing, manipulating, and visualizing data. Having these foundations you will be ready for machine learning and deep learning with Julia which will be in my upcoming lectures. Please stay tuned.
Who this course is for:
- You may be an adept data scientist well-versed in Python or R, or you might be embarking on your learning journey, grappling with the choice of a programming language. I will try to convince you that, you can accomplish everything, and even more, with Julia compared to what you can do with Python or R, all with the same level of ease. Moreover, Julia offers significantly greater speed than both of them.