Do I need a degree in data science to find a job in the field?

While a data science degree isn't required to find a career in the field, getting a bachelor's or master's degree could be beneficial. In a degree program, you'll receive information on the latest trends within the industry and meet faculty and students who work within the realm of data science.

Do you need to know how to code to work in data science?

Yes, coding is essential to the work of data scientists. You may need to understand a variety of coding languages to conduct your work effectively.

Should I learn Python or Java first?

Starting with Python first is typically the best way to begin learning programming languages, as it's simpler and more accessible than Java. However, both Python and Java are important languages to understand for a successful career in data science.

Top programming languages for data science

By: Nancy Finney, Edited by: Luke Daugherty

Published: February 14, 2025

Are you considering a career in data science? The field requires knowledge of different programming languages and a detailed understanding of coding. Your familiarity with programming is crucial for success if you're pursuing a job in the data science field.

Discover which programming languages are most important for data scientists to know so you can better collect and analyze data.

What are data science programming languages?

Data scientists use programming languages to aid in their analysis of various technologies. As a data scientist, you'll conduct mathematical and statistical analyses to gather information and data. You'll use various programming languages to interact with computers, develop processes, and gain access to information.

Various languages apply to data science work in natural language processing, geospatial analysis, network analysis, deep learning, and machine learning.

Which programming languages should data scientists know?

Python

Python is a beginner-friendly language with simple and easy-to-learn syntax. It is often used for web development and design, data analysis, machine learning, and creating computer software. Python is known as the most versatile and popular programming language for data scientists.

Structured Query Language (SQL)

Structured Query Language (SQL) is used for managing and interacting with databases. This programming language allows users to store and manipulate data based on queries. SQL works well with relational databases such as MySQL, SQLite, and PostgreSQL. You can use its simple syntax in a variety of settings.

R

R is a free open-source language primarily used for data visualization and statistics computing. The language supports data scientists with cleaning and storing data and is considered a main competitor of Python programming language.

Virtual Basic for Applications (VBA)

Virtual Basic for Applications (VBA) is a programming language that helps users automate tasks and modify or enhance various Microsoft Office programs. VBA is often used for repetitive tasks and helps to streamline and automate systems, therefore removing duplication in effort.

Julia

Julia is a programming language designed for technical and numbers-based computing. It was created as a high-level language with a technical focus. Julia is also used as a synthesis tool for low-level programming systems, hardware, and web programming.

Java

Java is a popular, versatile, and heavily used programming language for developing applications, software, and mobile apps. It is useful for many applications including games, cloud-based systems, and enterprise software.

C/C++

C and C++ are general programming languages known for their speed, making them ideal for software applications. Although they are more challenging to learn, mastering C and C++ will greatly improve your programming skills and open career pathways in data science due to the high demand for experts in these languages.

Get started in data science on edX

Through programming languages, data scientists can manipulate data, extract relevant information, automate tasks, and enhance data analysis through data visualization. If you're serious about becoming an expert in the field of data science, then pursuing an advanced degree may be a good call. Check out edX's array of advanced degree programs, so you can explore what you can do with a master's in data science degree.

Frequently asked questions about top programming languages for data science

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