閉じるボタン Login as
Member / Promoter

[KIT] Top programming language for Data Science

The demand for data scientists in every industry is growing significantly in the last decade. Why is data science so important? There is a need to assess and analyze the data you gathered in order to develop and improve every sector of a business.

Data science is a field or concept that uses scientific methods, processes, algorithms, and systems to extract and gain insights from many structural and unstructured data. It engages theories and techniques drawn from various fields such as statistics, mathematics, computer science, and information science.

Data scientists require both the right tools and a perfect skill set to produce the best results and insight with the available data. Various potential programming languages being used to bring out the best result, aspiring every data scientist to master.
Here are some of the best Programming Languages you should master as a data scientist.

  1. Python
    Python is an extremely popular general-purpose language that is widely used within the data science community. The reason behind its popularity is how easy it is to learn and use the language. It has the most simple and easy-to-read syntax among many programming languages.
    Python contained some of the best libraries for advanced technologies such as artificial intelligence, machine learning, data visualization, data processing, and predictive analytics.
  2. R
    R is one of the most often used tools in Data Science after Python. R is an open-source language and a software environment for statistical computing and graphics. R provides many statistical models with the public R package achieve, containing more than 8000 contributed packages, that can be utilized to all your needs.
  3. Java
    Java is an extremely popular general-purpose language that runs on its own Java Virtual Machine(JVM). Java is widely used due to its strong-typed syntax making it easier to manage large data sets.
  4. Scala
    Scala, another general-purpose language that is built on top of Java is also used among data scientists. Just like Java, it has a strong-typed syntax and also runs on JVM.
    However, Scala is often preferred over Java due to the fact that it offers more advanced machine learning and artificial intelligence libraries.
  5. SQL
    SQL, Structured Query Language, is a query language most widely used for managing and manipulating data held in a relational database management system. SQL is a very powerful language that is used to manage very large databases, it can retrieve 100 thousands of data within seconds.
    SQL skill can be the biggest asset for machine learning and data science professionals, as SQL is the most preferred language for managing databases in most organizations.

The field of data science is evolving very quickly throughout the year, tools used for extracting value from data science have also increased in numbers. Learning any one of the above-mentioned programming languages will surely kick off your data science career. Though there is no specific order to this list, Python and R are fighting for the top spot. If you are unsure of what to learn, you can try learning diving into 2 or 3 languages, and see what fit you best. Having more than one language skill will also show how versatile and competent you are as a data scientist.

Related posts

  1. [KIT] Why Learning English so important

  2. [KIT] How employees learn culture

  3. [KIT] MONOPOLY

  4. [KIT] Why Bright Edu is useful for student.

  5. [KIT] How to become a good presenter?

  6. [KIT]Full stack developer service

PAGE TOP