What Programming Languages Are Vital For Data Science?

As the data science field is evolving rapidly, there are high chances for you to get a high-paying job if you master more than one programming language. Here are some of the best programming languages for data science.

1. Python

Python is a general-purpose programming language that is used for a wide variety of data science tasks. It is an open-source language and is great for automating multiple tasks quickly. Python includes a sizable library of modules that are primarily used for data analysis, data visualization, and ML. Python is relatively easy to learn, so you can master it within a short time. For data science jobs, you need to have advanced Python skills as this language is used for data analysis, data visualization, ML, etc.

To expand your skills and knowledge of Python, the below comprehensive articles can be a valuable resource:

• Python tutorial
• Learn Python programming
• Python projects
• Python programs
  

2. Structured Query Language (SQL)

Structured Query Language (SQL) is a database language that people who want to get into the data science field should learn. You need to master SQL to get into a data science career as this language is mainly utilized for accessing and examining data from various databases. It is the ideal choice for data querying and data manipulation. With SQL, you can automate various tasks such as summing up averages, grouping data, discovering the minimum and maximum values in datasets, etc.
If you want to gain a better understanding of SQL, you can find plenty of information in the following informative articles:

• SQL tutorial
• 30 days of SQL
• SQL injection
• SQL advanced functions
  

3. R Programming

R is one of the best scripting languages and advanced programming languages that is widely supported. This open-source language has numerous libraries, R packages, and coding tools that are ideal for complicated and quantitative applications. R programming is generally the best choice for statistical analysis and statistical computing tasks with mathematics and graphics, so you must have advanced skills in R language for data science jobs.
If you want to learn more about R programming, you can go through the detailed articles listed here:

• Learn R programming
• Clustering in R programming
• AB Testing With R programming
• Data Handling in R programming

4. JavaScript

JavaScript is an easy-to-learn, object-oriented programming language which also comes with a good amount of libraries. This scripting language is utilized for a wide variety of tasks, such as data analysis, machine learning, data mining, etc. JavaScript is the best option for integrating applications into big data science development projects. Fundamental knowledge and skills of JavaScript is enough for a data science career.
Expand your knowledge of Javascript by checking out these extensive Javascript articles:

• Javascript complete guide
• Introduction to Javascript
• Debugging in JavaScript
• JavaScript variables and datatypes

5. C/C++

It’s recommended for data scientists to learn the C/C++ programming language. Having strong C/C++ skills makes it easy for you to collect data swiftly without any difficulty. This programming language is the ideal option for data science projects that require high stability or performance. . If you want to become a data scientist, it is vital to have a solid foundation of C/C++.

For entry-level data science jobs, it would be enough if you knew the fundamentals of these programming languages. However, it is vital to possess extensive knowledge of these programming languages for senior-level data science jobs.
If you are interested in learning more about C/C++, you can read the below comprehensive articles on C/C++ programming:

• C++ programming
• Introduction to C++
• First C++ program
• C++ tricks for competitive programming
  

Data science is one of the latest emerging fields with high potential growth. The adoption of cloud-based solutions and the usage of big data are driving growth for the data science industry. The market size of data science in 2022 was USD 122.94 billion, and it is estimated to surpass USD 942.76 billion by 2030.

Because of the market potential of data science, many people want to get into the data science industry and enhance their career options. There is a high demand for various data science jobs, including data engineer, data scientist, data analyst, data architect, etc. Beginners and even working professionals from non-programming backgrounds want to know if coding is required to get a job in the data science industry.