Data Science demand in the market is rapidly increasing from the last 5-6 years. For achieving proficiency in this field, there is a dire need of skilled persons who have good knowledge of data science programming languages and basic algorithms that data scientists must aware of. Data science is considered the best job in the United States for the last three years according to the Forbes report. Moreover these jobs will increase in 2020 almost by 28.3% approximately according to IBM studies. With the rapid advancement in technology data, science and machine are gaining popularity among different masses. For learning data science firstly achieving mastery in any one of the following languages is desired. Here we represent the top 8 data science programming languages that are very much needed for the new beginner in data science who want to opt data science as his/her career.
Talking about R programming firstly realize what is R? R foundation explained R as great language and tool for performing statistical computing and graphics. There is a different organization that supports R programming like RStudio, Microsoft, etc. For exploring, modeling and visualizing data, R programming gives operators, objects and functions.R programming is also used for prediction. Statistical methods are very tranquil to use and its implementation is also not so difficult even a beginner in programming can also easily learn it.
Python is very famous these days among users and data scientists. It is free and open-source. It is considered a versatile language as it is highly readable, has great memory management. It gives a great performance and it supports object-oriented programming. Python has inbuilt libraries that help in problem-solving. Python has libraries for solving basic steps of problems as well as it has advanced libraries such as TensorFlow and Keras as well.
SQL stands for Structured Query Language. It is very much necessary that a data scientist know SQL as it is needed for extracting and wrangling up the data. For achieving proficiency in data science the important thing is knowing how to retrieve relevant data from chunks of data. Learning SQL allows you to extract data from differently organized resources.SQL is available in various forms like SQLite, MYSQL, etc. It is deployed for querying data that is stored in a relational database management system.
JAVA is most used and one of the oldest languages that are deployed for programming. It is so popular programming language that executes on JVM(JAVA VIRTUAL MACHINE). It contains libraries that support machine learning as well as data science. It is a computing system that is supported by oracle.
Julia is a recently developed language. It is used for solving complex mathematical problems. It almost contains more than 19000 packages. For processing large chunks of data Julia has a great speed of execution. It is faster than python as well as c language. It provides the best results for numerical as well as parallel computing.
MATLAB is a great language for statistical analysis, developed by Mathworks ensures various algorithms that are proven as a boon for mathematicians in solving complex problems based on signal processing, matrix algebra and image processing.
TensorFlow is a very good framework for processing large scale of data. It also supports the training of neural networks on large training sets in very less period which in turn works with distributed computing.TensorFlow is developed by Google allowing it to execute various functions in an optimized way either on CPU or GPU.
Also check: Top 7 Programming Language
Data Science is an emerging field of technology that will come up with innovations in the coming years. For achieving excellence in it, you should excel yourself first in any of the above-explained programming languages. We have described the top 8 data science programming languages that can help you to learn data science in a better way. There are some other languages as well but these are more trendy and easily deployable.