Top Data Science Programming Languages

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September 23, 2022
5 min read

If you have ever wondered why Data Science is necessary, then you are not alone. The power of data science allows businesses to create products that consumers love. For example, an eCommerce company can learn about customer personas by analysing their purchasing habits. It will also enable businesses to improve banking, transportation, manufacturing, and other business processes.

Why is learning programming a must for data science?

Working knowledge of programming languages is essential to succeed in data science. Python is one of the most popular programming languages, so if you're interested in working in this field, gaining programming skills is a good start. The skills you acquire through daily coding will eventually help you solve complex data science problems.

Future Programming Languages For Data Science

Data scientists need to be productive and efficient, which is why they need a programming language that can do the job. There are hundreds of programming languages, but some are better suited for data science projects than others. Here is a list of the top data science programming languages to look out for in the future.

  1. Python
  2. Java
  3. Scala
  4. R
  5. C/C++
  6. Javascript
  7. MATLAB
  8. Javascript

Most Used Programming Languages For Data Science

There are many different programming languages used in data science. Some of the most used programming languages For Data Science include Python, R, and Scala. Other languages may be used for specific tasks, such as creating dashboards. These programming languages vary in their ease of use and complexity. If you're new to data science, it can be challenging to determine which programming language to learn. Data science's most common programming languages are Python, SQL, and R. However, you don't have to stick to one programming language or another. There are other options available that can be more beneficial to your needs.

  1. Python - The most popular programming language used in data science. It supports machine learning, deep learning, artificial intelligence, dynamic typing and binding. It is also transparent and easy to learn. It is ideal for new programmers.
  2. Scala: Scala is a high-level programming language for big data compatible with the Java ecosystem. The language is object-oriented and supports concurrent processing. The language has many libraries that can perform various data science tasks.
  3. R - Its capabilities include supporting time-series analysis, which can be used to predict stock market movement or credit risk. Advanced processing and visualisation tools allow for an easy understanding of results and trends.
  4. MATLAB - A programming language that supports matrix and vector operations is essential for data scientists and machine learning practitioners. Its main functions are mathematics, signal processing, graphing, and matrix manipulation. Unlike R, which requires additional packages, Matlab's syntax is much more streamlined and intuitive.

Python and R are popular Big Data programming languages that can help you build data-driven applications. These languages are both suitable for beginners with no previous coding experience and offer many resources to help beginners get started. Newton School also offers guided projects in both R and Python to provide a hands-on introduction to these languages.

The statistical programming language R is famous for data visualisation and analysis. It offers various functions, including linear and nonlinear modelling, classification, clustering, and time-series analysis. Data scientists use these tools to analyse data and create predictions. The language supports various types of statistical analysis and machine learning. Two of the most popular statistical programming languages are Python and R, but other languages, including Java and Scala, can also be used for these purposes.

Newton School

Currently, there is a massive talent gap in the Data Science field. To address this, Newton School has created an online platform that offers a personalised learning platform. The school's mission is to bridge this gap by creating a customised learning environment and tackling the severe problem of the employability of graduates.

The school has a proven track record, with over a thousand placements in less than two years. It has hired over 350 companies, including Google, Deloitte, Zomato, Nutanix, and Mphasis.

The most popular courses of Newton School are -

  1. Newton School Full-Stack Development Course - The Full Stack Development Course in Data Science at Newton School provides training and hands-on experience in data science, programming and computer science. Getting a full-stack developer certification is not as difficult as it might seem. A full-stack developer course can be completed online and includes project-based learning. You'll need to complete mini-projects and practice your coding skills until you're confident enough to move on to the capstone project. Your capstone project can be a fully-functional web app, like Oyo or MakeMyTrip. Your capstone project will also require good research skills and copious notes.
  2. Newton School Master in Computer Science (MIA University) - Newton School's Master of Computer Science (MCS) program, in collaboration with MIA University, provides an excellent education and career opportunity for people interested in data science and cybersecurity. The program's innovative model focus on the combination of theoretical and hands-on learning. In addition to learning data science and cybersecurity, students will gain knowledge of big data analytics and data science.
  3. Newton School Master in Data Science (IU University) - The program is designed to help students apply their mathematical and statistical knowledge to data science problems. It requires students to have basic programming skills in Python and a general understanding of mathematics. Students who don't have these skills are encouraged to take a course called Data Science Essentials first.
  4. Newton School's Full-Stack Development Pay After Placement - In this course, students will learn how to work with databases, REST APIs, and other topics that are relevant to the field. Once they complete their studies, they'll be ready to build their websites and apps. Newton School's unique payment model is designed to close the gap between education and employment. Students don't have to pay an upfront fee and instead pay their tuition only after being placed. This unique payment model allows students to pursue a career in the field they love.

Why is Data Science necessary for the Future?

The need for data scientists is increasing, and the field is growing in popularity. Today, the digital world is filled with data, and it is becoming more critical for businesses to make informed decisions.

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