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Top Programming Languages For Machine Learning Based On AIM Research

Top Programming Languages For Machine Learning Based On AIM Research

Ambika Choudhury

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While entering into the data science field, newbies are always stuck at that one question: what programming language one should learn and whether the language is suitable. Ever year Analytics India Magazine conducts surveys in order to gain insights on the trending tools and toolkits and other aspects in the data science field. The surveys are responded by machine learning enthusiasts, developers and data scientists, among others, from the community across India. The opinions are taken from all those who practice data science, from professionals with less than two years of experience to CXOs in order to get a thorough idea of the working environment in this growing field.

According to the Data Science Skills Study, languages like Python, R, and SQL have been trending for quite a few years now. According to the survey on Data Science recruitment in India, other languages like C, Java, Julia, Scala, among others are gaining less traction in the field of data science. In the case of analytical tools, SAS, Matlab, among others have been trending in the market. Based on these two pieces of research, we are unpacking the list of key programming languages that a data science developer mus know to find success:


According to our surveys, Python continues to be the most popular language for data scientists. In 2018, almost 44% of the professionals claimed that they use this language at the most. In the case of using the general-purpose library of Python, libraries like Pandas, NumPy, Sklearn, and MatPlotLib emerged as a clear choice for most data scientists at almost 41%, 24%, 17%, and 14% respectively.  

This year, the graph for using this language has exponential growth. It continues to be the most popular language in the industry in 2019 with its popularity growing to 68% from 44%. Talking about the Python libraries, the above-mentioned libraries emerged as the clear choices for most data scientists but this time NumPy followed the growth of 30% from 24%.

Also, in our annual survey on data science recruitment in India, last year there was a tough fight between the two programming languages, Python and R with 48 and 39% respectively. This year, Python proved to be one of the important skillsets to be a data scientist and almost 75% of respondents talked about the importance of Python in data science.

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R, the open-source programming language is considered to one of the most popular language in the field of data science. This language is used in analysing both structured and unstructured data. After Python, R is the next most popular programming language. In our annual survey on data science recruitment in India 2018, 39% of respondents claimed R to be a must-know programming language for an aspiring data scientist. However, this year it has been claimed by only 18%.


According to our survey on the Data Science skill study, SQL (Structured Query Language) which is a standard database language is preferred by 6% and 4% of respondents for the year 2018 and 2019 respectively. This language is considered as one of the important toolkits in a data scientist toolbox. To be more precise, this language is usually used by the data analysts than the data scientist. 


Currently, Python programming language is ruling over emerging technologies and it will continue to rule for several years now. However, change is the only constant we know and in time there may be some other language which will succeed Python’s monopoly. Moreover, one most important point is that using a programming language depends upon the system or software that one is trying to build.

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