Do you know how social media platforms generate ads or suggestions based on your interests? How do health bots or virtual assistants work? In both cases, the technologies that came into play are machine learning and data science. Today, there is a tremendous demand for skilled professionals in these fields. So, it is the right moment to make the most of this opportunity by learning the programming languages used for these two. Let’s explore the top 6 programming languages for data science and machine learning.
 
1. Python
This lightweight and versatile programming language is widely used in data science and machine learning. Python is not only open-source and easy-to-use but is also dynamic and supports both structured and functional programming. Its simplicity has always caught the attention of data scientists and machine learning programmers. Moreover, Python is scalable and has various visualization packages and core libraries that make coding a breezy affair. 
 
2. JavaScript
JavaScript is the multipurpose language that has long been used successfully by machine learning programmers. With its strong frameworks, such as Weka, Rapid Miner, and more supporting machine learning algorithms and regression techniques, Java Script has proven its worth. The object-oriented programming language is also found very suitable for creating dashboards and visualization of data. 
 
3. Scala
Although this elegant programming language was initially designed to find a way to support both functional and object-oriented programming, it is now ably used by programmers to handle big data. Based on Java Virtual Machine, Scala is lightning fast in data processing and enables better memory management. It also offers more analytics power for vast data volumes like Petabytes and Zettabytes. Now, this is incredible!  
 
4. R  
Developed in 1991, R is basically a high-level programming language used initially for statistical computing. However, it has now the best tools to work for machine learning projects and has found varied applications in data science like the exploration of data sets, ad hoc analysis, etc. Its only drawback is the steep learning curve, but it is powerful which makes it apt to serve the desired purpose. 
 
5. SQL
Structured Query Language is considered one of the most popular programming languages for data query, storage, manipulation, and retrieval in relational databases. However, many still refer to SQL more accurately as a powerful data management tool that has significant importance in data analytics and machine learning. 
 
6. Julia 
As a high-level language, Julia is intentionally developed for speedy analysis of numerics. With its easy syntax and high performance, Julia has emerged as an excellent language for server-side and client-side programming. Moreover, it can be executed seamlessly on varied platforms and is easily understandable. This makes it ideal for data science and machine learning. 
 
Out of these, you must learn and master at least two programming languages to realize various data science and machine learning functions. Enrolling yourself in a Data Science & Machine Learning training course will help you immensely in this endeavor. There are now plenty of training institutes where you can learn from skilled faculty in either online or offline mode.