Data Science | Tools To Learn Other Than Python

Python is a popular and versatile programming language that is widely used in data analysis, machine learning, and scientific computing. However, it is important for data analysts to learn other languages as well to expand their skills and be more versatile in their careers. Here are a few languages that data analysts might consider learning after Python:

 

  • R: R is another popular language for data analysis and statistical computing. It has a large ecosystem of packages and libraries for data visualization, modeling, and machine learning. It is also widely used in academia and research.

 

  • SQL: SQL (Structured Query Language) is a programming language used for managing and querying relational databases. It is essential for working with large datasets and is widely used in data analysis and business intelligence.

 

  • JavaScript: JavaScript is a programming language used for creating dynamic and interactive web pages. It is also widely used for data visualization, such as creating interactive charts and maps. Familiarity with JavaScript can open doors to opportunities in web development, data visualization, and big data analysis.

 

  • Scala: Scala is a programming language that runs on the Java Virtual Machine (JVM) and is widely used in big data processing. It is an efficient and powerful language that is used in Apache Spark, a popular big data processing framework.

 

  • Julia: Julia is a newer programming language that is gaining popularity in the data science community. It is designed for high-performance numerical computing and is well-suited for big data and machine learning.

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I share tips and tricks in my blog that I have learnt in over and a half decade. I share practical use of Machine Learning that I use in my daily project. My blog is further categorised into four distinct areas including Tourism, Education, Machine Learning, and Health. 

Ultimately, the best language to learn after Python will depend on the specific needs and goals of the data analyst. Learning a new language can be challenging, but it can also open new opportunities and make you more valuable in the job market. It’s important to consider the specific needs of your organization and the projects you will be working on before deciding on a new language to learn.

 

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THIS POST IS WRITTEN BY SYED LUQMAN, A DATA SCIENTIST FROM SHEFFIELDSOUTH YORKSHIRE, AND DERBYSHIREUNITED KINGDOMSYED LUQMAN IS OXFORD UNIVERSITY ALUMNI AND WORKS AS A DATA SCIENTIST FOR A LOCAL COMPANY. SYED LUQMAN HAS FOUNDED INNOVATIVE COMPANY IN THE SPACE OF HEALTH SCIENCES TO SOLVE THE EVER RISING PROBLEMS OF STAFF MANAGEMENT IN NATIONAL HEALTH SERVICES (NHS). YOU CAN CONTACT SYED LUQMAN ON HIS ,TWITTER, AND LINKEDIN. PLEASE ALSO LIKE AND SUBSCRIBE MY YOUTUBE CHANNEL.

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