Join the Julia Track
Julia is an open-source high-level, dynamic programming language whose sweet spot is technical and scientific computing. It is convenient for day-to-day work and fast enough for high performance computing.
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Track mentors

11 Mentors

Our mentors are friendly, experienced Julia developers who will help teach you new techniques and tricks.
Track students

5,653 Students

Join thousands of students who have enjoyed learning and improving their skills by taking this track.
Track exercises

51 Exercises

Hundreds of hours have gone into making these exercises fun, useful, and challenging to help you enjoy learning.

About Julia

function julia_set(z, c)
    n = 0
    while abs2(z) < 4
        z = z^2 + c
        n += 1

The creators of Julia want to eat their cake and have it too. As they describe in their blog post "Why We Created Julia" they want the speed of C, the dynamism of Ruby, the familiar mathematical notation of Matlab. They want it to be their favourite things from their favourite languages. String processing like Perl. Glue like the shell. Powerful but not impenetrably complex.

Julia has a powerful, yet clear and intuitive, dynamic type system. It allows writing dynamic code and specifying types if additional expressiveness is needed for simplification or performance increases. The language features multiple dispatch, meaning it chooses which method is called based on the types of each argument. This lets you write specific methods for certain types while providing generic fallbacks and is particularly useful for mathematical code, where it is not clear why an operation should belong to a specific argument.

Metaprogramming is easy in Julia. Code can be represented as a data structure in Julia itself, so a program can transform and generate its own code, similarly to Lisp. Large parts of Julia's base and standard library are also written in Julia. Understanding and changing it does not require knowledge of another language. If a library you need to use is written in another language, such as C, Fortran or Python, you can use simple interfaces to call them directly from your code.

Despite its young age, Julia is already being used in the real world in a variety of fields, such as but not limited to Finance, Data Science and Scientific Computing. You can find many showcase applications on the Julia Blog Aggregator, case studies from commercial use on juliacomputing.com, and a list of publications about the language and its applications in research here.

Join the Julia track

Exercism is a great website

What I like about it is that I am able to solve the challenges in a TDD way working in a environment that I am familiar (my own PC not a browser IDE) and the cherry on the top of the cake is that I have access to code reviews.

Relaxed. Encouraging. Supportive.

Meet the Julia Track mentors

Once you join the Julia language track, you will receive support and feedback from our team of mentors. Here are the bios of a few of the mentors of this track.

Avatar of Seth Bromberger

Seth Bromberger Homepage

I am the founder of JuliaGraphs and one of the core developers of LightGraphs.jl. I've been using Julia at work and for personal projects since v0.3.
Avatar of Jeffrey Sarnoff

Jeffrey Sarnoff https://github.com/JeffreySarnoff

I contribute packages to The Julia Community, and, perhaps, help to you.
Avatar of François Févotte

François Févotte https://github.com/ffevotte

Co-founder and Chief Scientist of TriScale innov, a startup dedicated to technical and scientific computing. I have been using Julia routinely for the past few years, and try to contribute back by being involved in the development of a few packages.
Avatar of Miguel Raz

Miguel Raz https://github.com/miguelraz

¡Hola! I am a Mexican physics student who loves to use Julia for High Performance Computing. Pull Requests welcome!
Avatar of Gajendra Deshpande

Gajendra Deshpande Home page

I have delivered talks at JuliaCon 2018, 2020 and various Python conferences worldwide. I use Python and Julia extensively for teaching and research. My major work includes using Python and Julia to develop prototypes in the field of Cyber Security and Artificial Intelligence. I lead PyData Belagavi and OWASP Belagavi chapters. I love to mentor students and volunteer at Free and Open Source events.
Avatar of Thomas Kahn

Thomas Kahn https://github.com/thomasbkahn

As a Data Scientist, I found Julia to be very powerful in my own work and I am excited about its future. It's the perfect time to start learning Julia now that version 1.0 has been released.
Fun. Challenging. Interesting

Community-sourced Julia exercises

These are a few of the 51 exercises on the Julia track. You can see all the exercises here.

Reverse String
text formatting
data structures
functional programming
Matching Brackets
data structures
Spiral Matrix
exception handling
ISBN Verifier
Passionate. Knowledgeable. Creative.

Meet the Julia Track maintainers

The Julia Maintainers are the brains behind the Julia Track. They spend their spare time creating interesting and challenging exercises that we can all learn from. We are incredibly grateful for their hard work. Here are the bios of a few of the maintainers of this track.

Avatar of Colin Caine

Colin Caine My Github

I write code for scientific papers (computer science and social science) and commercial projects in Julia. It's my favourite language and I'm happy to help a few more people learn it!
Avatar of Logan Kilpatrick

Logan Kilpatrick My Github

I began using Julia when I was getting started as a Software Engineering Intern at NASA. Since then, I have gone on to Intern with Julia Computing on the PumasAI project, win a new Julia Language contributor award for 2019, and authored a few small packages. The Julia programming language and community are incredible. I am looking forward to helping more in the future.
Avatar of Sascha Mann

Sascha Mann My website

Physics student. Learned about Julia in a class and decided to dig more into it. Very promising language and I wanted to get involved in its community.

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