The Julian Way of Programming and How It Applies to Data Science

For those interested in delving deeper into the Julia language, for data science projects, this video offers a comprehensive introduction to the key aspects of it. Without making any assumptions about your programming background (apart from just the one, that you have some programming experience), we look into the characteristics of the language that make it what it is, and how they can facilitate your data science process, should you incorporate Julia in it. Namely, we look into functional programming, multiple dispatch, Julia’s user defined types, and the basics of parallelism. Upon watching this video, you’ll feel more confident about this powerful tool, and more empowered to work the data using it, like never before!

We will cover:
What is Julia anyway? This includes the early years of Julia, Julia’s current state, the future of Julia language, and Julia’s role in the programming world.
How Julia fits in the Data Science process
Functional programming
Multiple dispatch
Julia’s user defined types
Parallelism basics in Julia
Next steps including what’s next in the Julia universe, what you can do once you get the hang of Julia, and resources for further development