The Julia Programming Language: Uses, Benefits, and Careers

Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and Alan Edelman developed the Julia programming language in 2012 to create a general-purpose, open-source language to support high-level, dynamic programming in scientific domains. They combined their favorite aspects of MATLAB, Python, R, and Perl to form Julia. Today, Julia is primarily known as a scientific programming language, and users often tout it as a language well-suited to computing with large-scale numerical needs. 

Explore the basics of Julia, its popular uses, and the careers you might pursue that need Julia.

What is Julia?

This high-level, high-performance programming language offers speed and performance for technical and numerical computing. Colleagues at MIT developed Julia to address the limitations and trade-offs often encountered when working with languages like Python, MATLAB, and R, where users experience a trade-off between code readability and execution speed.

While these other scripting languages could support productivity, they proved slower when executing programs requiring high-level mathematics or technical computing. This lagging speed led many developers to migrate their code into another program to achieve their desired speeds. Yet, this could undermine efficacy. Julia came about to address this “two-language problem.” With Julia, developers avoid having to transition from one language to another.

What is the Julia programming language used for?

Julia is particularly well-suited for tasks such as numerical simulations, data analysis, machine learning, and scientific computing, where performance is crucial. 

Julia offers faster LLVM (low-level virtual machine) due to its just-in-time (JIT) compilation and better memory management, giving it impressive speed and math-friendly syntax. This has helped it gain popularity in finance, engineering, physics, and machine learning fields for its execution of: 

• Computing involving Algebra and other numerics

• Machine learning and artificial intelligence

• Data science

• Distributed and parallel computing

• Web development

• Organizational research

Features of the Julia programming language

Julia is an open-source project known for its high performance and ability to generate highly efficient code at speeds approaching those of languages like C and Fortran. A dynamic language, Julia is relatively easy for programmers to learn and adapt. Although relatively young, since its release in February 2012, Julia has built a community of over 1,000 contributors.

Julia's multiple dispatch type system makes it easy to express object-oriented and functional programming patterns. This allows developers to write more generic code that can automatically adapt to different types of data, improving code reusability and extensibility. You can also use the Python, R, C/Fortran, C++, and Java libraries.

Julia also provides libraries for data manipulation, machine learning, analysis, parallel computing, and visualization, which are essential for scientific computing and data analysis tasks. 

Advantages and disadvantages of using Julia

When weighing the value of learning the Julia language, consider the pros and cons. Understanding Julia’s unique advantages and drawbacks can help you decide whether to invest your time and effort.

Julia programming pros

New and free, Julia combines programming simplicity with high-level capabilities. Other Julia programming pros include the following: 

• Computational speed

• New, advanced computing packages 

• Advanced features, such as multiple dispatch, differentiable programming, dynamic and declarative type system

• Homoiconic capabilities that facilitate metaprogramming

• Support for Python, C, and Fortran packages 

Julia programming cons

Nevertheless, you could also encounter some challenges working with Julia. Some potential cons to the language include:

• Difficulties when reading CSV files

• Some alternative features have design flaws that impact performance

• Slower compiling speed 

• Less community support than other programming languages

Companies and projects that use Julia

Globally, people use Julia to enjoy high-level capabilities with high efficiency. Institutions such as Stanford, Cornell, UC Berkeley, Brown, and MIT teach this programming language. Organizations using Julia include the following: 

• NASA

• IBM

• Microsoft

• Google

• Ford

• Pfizer

• KPMG

• Capital One

Julia programming jobs  

You can find several different types of careers that require an understanding of Julia. As an increasingly popular programming language, Julia’s scalability allows it to stand out as an option to meet the programming needs of numerous applications across different industries.

Data scientist

Average annual US salary: $114,282.59 [1] 

Job outlook (projected growth from 2022 to 2032): 35 percent [2]

Data scientists determine what data a project needs, collect and categorize it, and then provide clean, accurate, reliable data sets for analysis. They may perform analysis in some roles, using text and visualizations to explain the main findings. You’ll play a crucial role in uncovering actionable insights from data and help companies and decision-makers devise data-driven strategies and solve real-world problems across various industries.

Operations research analyst 

Average annual US salary: $96,627.50 [3]

Job outlook (projected growth from 2022 to 2032): 23 percent [4]

As an operations research analyst, you’ll use data to identify problems in areas such as business, logistics, health care, or other fields. You collect and organize information from various sources, analyze that collected data, and report back the relevant information you can extract from the data.

Computer and information research specialists

Average annual US salary: $155,875.20 [5] 

Job outlook (projected growth from 2022 to 2032): 23 percent [6]

Computer and information research specialists innovate new and existing computing programs and information systems. They explore complex problems and develop theories of new ways to address them. Doing so can require reliance on complex algorithms, so these scientists would use Julia to make their work more efficient.

Database administrator

Average annual US salary: $101,895.68 [7]

Job outlook (projected growth from 2022 to 2032): 8 percent [8]

A data administrator manages an organization's data resources throughout their lifecycle. In this position, you will design and implement databases, ensure data security and integrity, oversee data backups and recovery, optimize data storage and retrieval processes, and maintain data documentation and metadata. You’ll ultimately ensure the organization's data assets are well-organized, accessible, and aligned with business needs and regulatory requirements.

How to learn Julia 

You can learn Julia in many different ways. The official Julia website includes resources like Julia Academy, Julia Language’s YouTube channel, and a growing list of Julia tutorials. Other learning methods include the following:

• Exploring Julia documentation online

• Watching Julia tutorial videos

• Reading books on Julia

• Joining the Julia community

• Taking on basic Julia projects

How to download Julia programming language

One of the quickest ways to download Julia is to go to the official website download page at https://julialang.org/downloads/. The webpage automatically detects your operating system and gives you a command to run in your computer’s command line interface. 

The command for a Linux/MacOS system is: curl -fsSL https://install.julialang.org | sh

The command for a Windows system is: winget install julia -s msstore

Julia works with VS Code, Jupyter, Pluto.jl, Vim, and Emacs IDEs. 

Next steps on Coursera.

Julia is a powerful programming language for data scientists, operational research scientists, machine learning, and high-level computations. 

Expand your data science knowledge and relevant skills with online courses that can help you choose a career path that meets your goals. For example, you can explore the topic in detail with the IBM Data Science Professional Certificate on Coursera, which can take you from beginner to career-ready in several months.