5 must learn programming language for data science and machine learning professionals
Learning programming languages is the first step in becoming a data scientist or machine learning expert. You should be familiar with several programming languages for your practical work and self-learning. This post briefly overviews the top must-know programming languages for data science and machine learning professionals.
R Programming Language
R is open source software, free of charge, released under the GNU General Public License. The latest stable version is R 3.4, with minor updates released every six months. There are also many packages on CRAN (Comprehensive R Archive Network), which provide additional functionality when working with data sets in R itself. It is used extensively in academic environments to teach statistical methods and to develop statistical software.
Python is a programming language for web development, data analysis, and machine learning. It's also one of the most popular languages to learn as a beginner, thanks to its simple syntax and readability.
It is a high-level programming language with dynamic typing that makes it easier to write programs using fewer lines of code than other languages like C++ or Java. The syntax is not complicated, so you can learn how things work without getting lost in technical jargon or complex grammar rules that don't apply in real-life situations.
It is a structured query language used to create, read, update and delete data in a database. The SQL statements are written in English sentences or commands and separated by semicolons (;).
SQL has been for many years, and several variations exist across different databases, including MySQL, PostgreSQL, Oracle, etc.
Scala is a modern general-purpose programming language designed to express common programming patterns in a concise, elegant, and type-safe way. It is an immaculate language with an expressive syntax that makes it easy for developers to work with large amounts of data.
Java is a general-purpose, concurrent, class-based, object-oriented computer programming language designed to have as few implementation dependencies as possible.
This language is among the most popular in the Data Science industry. It has many advantages over other languages. It's easy to learn and still provides excellent performance when solving complex problems with Machine Learning algorithms.
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